Mitigating Observation Perturbation Sampling Errors in the Stochastic EnKF

KAUST Repository

Hoteit, Ibrahim; Pham, D.-T.; El Gharamti, Mohamad; Luo, X.

2015-01-01

The stochastic ensemble Kalman filter (EnKF) updates its ensemble members with observations perturbed with noise sampled from the distribution of the observational errors. This was shown to introduce noise into the system and may become pronounced when the ensemble size is smaller than the rank of the observational error covariance, which is often the case in real oceanic and atmospheric data assimilation applications. This work introduces an efficient serial scheme to mitigate the impact of observations’ perturbations sampling in the analysis step of the EnKF, which should provide more accurate ensemble estimates of the analysis error covariance matrices. The new scheme is simple to implement within the serial EnKF algorithm, requiring only the approximation of the EnKF sample forecast error covariance matrix by a matrix with one rank less. The new EnKF scheme is implemented and tested with the Lorenz-96 model. Results from numerical experiments are conducted to compare its performance with the EnKF and two standard deterministic EnKFs. This study shows that the new scheme enhances the behavior of the EnKF and may lead to better performance than the deterministic EnKFs even when implemented with relatively small ensembles.

Assessing human error during collecting a hydrocarbon sample of ...

African Journals Online (AJOL)

This paper reports the assessment method of the hydrocarbon sample collection standard operation procedure (SOP) using THERP. The Performance Shaping Factors (PSF) from THERP analyzed and assessed the human errors during collecting a hydrocarbon sample of a petrochemical refinery plant. Twenty-two ...

The predicted CLARREO sampling error of the inter-annual SW variability

Science.gov (United States)

Doelling, D. R.; Keyes, D. F.; Nguyen, C.; Macdonnell, D.; Young, D. F.

2009-12-01

The NRC Decadal Survey has called for SI traceability of long-term hyper-spectral flux measurements in order to monitor climate variability. This mission is called the Climate Absolute Radiance and Refractivity Observatory (CLARREO) and is currently defining its mission requirements. The requirements are focused on the ability to measure decadal change of key climate variables at very high accuracy. The accuracy goals are set using anticipated climate change magnitudes, but the accuracy achieved for any given climate variable must take into account the temporal and spatial sampling errors based on satellite orbits and calibration accuracy. The time period to detect a significant trend in the CLARREO record depends on the magnitude of the sampling calibration errors relative to the current inter-annual variability. The largest uncertainty in climate feedbacks remains the effect of changing clouds on planetary energy balance. Some regions on earth have strong diurnal cycles, such as maritime stratus and afternoon land convection; other regions have strong seasonal cycles, such as the monsoon. However, when monitoring inter-annual variability these cycles are only important if the strength of these cycles vary on decadal time scales. This study will attempt to determine the best satellite constellations to reduce sampling error and to compare the error with the current inter-annual variability signal to ensure the viability of the mission. The study will incorporate Clouds and the Earth's Radiant Energy System (CERES) (Monthly TOA/Surface Averages) SRBAVG product TOA LW and SW climate quality fluxes. The fluxes are derived by combining Terra (10:30 local equator crossing time) CERES fluxes with 3-hourly 5-geostationary satellite estimated broadband fluxes, which are normalized using the CERES fluxes, to complete the diurnal cycle. These fluxes were saved hourly during processing and considered the truth dataset. 90°, 83° and 74° inclination precessionary orbits as

Type-II generalized family-wise error rate formulas with application to sample size determination.

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Delorme, Phillipe; de Micheaux, Pierre Lafaye; Liquet, Benoit; Riou, Jérémie

2016-07-20

Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Sampling for quality assurance of grading decisions in diabetic retinopathy screening: designing the system to detect errors.

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Slattery, Jim

2005-01-01

To evaluate various designs for a quality assurance system to detect and control human errors in a national screening programme for diabetic retinopathy. A computer simulation was performed of some possible ways of sampling the referral decisions made during grading and of different criteria for initiating more intensive QA investigations. The effectiveness of QA systems was assessed by the ability to detect a grader making occasional errors in referral. Substantial QA sample sizes are needed to ensure against inappropriate failure to refer. Detection of a grader who failed to refer one in ten cases can be achieved with a probability of 0.58 using an annual sample size of 300 and 0.77 using a sample size of 500. An unmasked verification of a sample of non-referrals by a specialist is the most effective method of internal QA for the diabetic retinopathy screening programme. Preferential sampling of those with some degree of disease may improve the efficiency of the system.

Quantifying Configuration-Sampling Error in Langevin Simulations of Complex Molecular Systems

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Josh Fass

2018-04-01

Full Text Available While Langevin integrators are popular in the study of equilibrium properties of complex systems, it is challenging to estimate the timestep-induced discretization error: the degree to which the sampled phase-space or configuration-space probability density departs from the desired target density due to the use of a finite integration timestep. Sivak et al., introduced a convenient approach to approximating a natural measure of error between the sampled density and the target equilibrium density, the Kullback-Leibler (KL divergence, in phase space, but did not specifically address the issue of configuration-space properties, which are much more commonly of interest in molecular simulations. Here, we introduce a variant of this near-equilibrium estimator capable of measuring the error in the configuration-space marginal density, validating it against a complex but exact nested Monte Carlo estimator to show that it reproduces the KL divergence with high fidelity. To illustrate its utility, we employ this new near-equilibrium estimator to assess a claim that a recently proposed Langevin integrator introduces extremely small configuration-space density errors up to the stability limit at no extra computational expense. Finally, we show how this approach to quantifying sampling bias can be applied to a wide variety of stochastic integrators by following a straightforward procedure to compute the appropriate shadow work, and describe how it can be extended to quantify the error in arbitrary marginal or conditional distributions of interest.

Effects of Target Positioning Error on Motion Compensation for Airborne Interferometric SAR

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Li Yin-wei

2013-12-01

Full Text Available The measurement inaccuracies of Inertial Measurement Unit/Global Positioning System (IMU/GPS as well as the positioning error of the target may contribute to the residual uncompensated motion errors in the MOtion COmpensation (MOCO approach based on the measurement of IMU/GPS. Aiming at the effects of target positioning error on MOCO for airborne interferometric SAR, the paper firstly deduces a mathematical model of residual motion error bring out by target positioning error under the condition of squint. And the paper analyzes the effects on the residual motion error caused by system sampling delay error, the Doppler center frequency error and reference DEM error which result in target positioning error based on the model. Then, the paper discusses the effects of the reference DEM error on the interferometric SAR image quality, the interferometric phase and the coherent coefficient. The research provides theoretical bases for the MOCO precision in signal processing of airborne high precision SAR and airborne repeat-pass interferometric SAR.

Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation

International Nuclear Information System (INIS)

Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rydén, J.; Rochman, D.; Alhassan, E.; Pomp, S.

2016-01-01

In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also

Quantification and handling of sampling errors in instrumental measurements: a case study

DEFF Research Database (Denmark)

Andersen, Charlotte Møller; Bro, R.

2004-01-01

in certain situations, the effect of systematic errors is also considerable. The relevant errors contributing to the prediction error are: error in instrumental measurements (x-error), error in reference measurements (y-error), error in the estimated calibration model (regression coefficient error) and model...

Estimation of sampling error uncertainties in observed surface air temperature change in China

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Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun

2017-08-01

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.

The Impact of Soil Sampling Errors on Variable Rate Fertilization

Energy Technology Data Exchange (ETDEWEB)

R. L. Hoskinson; R C. Rope; L G. Blackwood; R D. Lee; R K. Fink

2004-07-01

Variable rate fertilization of an agricultural field is done taking into account spatial variability in the soil’s characteristics. Most often, spatial variability in the soil’s fertility is the primary characteristic used to determine the differences in fertilizers applied from one point to the next. For several years the Idaho National Engineering and Environmental Laboratory (INEEL) has been developing a Decision Support System for Agriculture (DSS4Ag) to determine the economically optimum recipe of various fertilizers to apply at each site in a field, based on existing soil fertility at the site, predicted yield of the crop that would result (and a predicted harvest-time market price), and the current costs and compositions of the fertilizers to be applied. Typically, soil is sampled at selected points within a field, the soil samples are analyzed in a lab, and the lab-measured soil fertility of the point samples is used for spatial interpolation, in some statistical manner, to determine the soil fertility at all other points in the field. Then a decision tool determines the fertilizers to apply at each point. Our research was conducted to measure the impact on the variable rate fertilization recipe caused by variability in the measurement of the soil’s fertility at the sampling points. The variability could be laboratory analytical errors or errors from variation in the sample collection method. The results show that for many of the fertility parameters, laboratory measurement error variance exceeds the estimated variability of the fertility measure across grid locations. These errors resulted in DSS4Ag fertilizer recipe recommended application rates that differed by up to 138 pounds of urea per acre, with half the field differing by more than 57 pounds of urea per acre. For potash the difference in application rate was up to 895 pounds per acre and over half the field differed by more than 242 pounds of potash per acre. Urea and potash differences

Learning from Past Classification Errors: Exploring Methods for Improving the Performance of a Deep Learning-based Building Extraction Model through Quantitative Analysis of Commission Errors for Optimal Sample Selection

Science.gov (United States)

Swan, B.; Laverdiere, M.; Yang, L.

2017-12-01

In the past five years, deep Convolutional Neural Networks (CNN) have been increasingly favored for computer vision applications due to their high accuracy and ability to generalize well in very complex problems; however, details of how they function and in turn how they may be optimized are still imperfectly understood. In particular, their complex and highly nonlinear network architecture, including many hidden layers and self-learned parameters, as well as their mathematical implications, presents open questions about how to effectively select training data. Without knowledge of the exact ways the model processes and transforms its inputs, intuition alone may fail as a guide to selecting highly relevant training samples. Working in the context of improving a CNN-based building extraction model used for the LandScan USA gridded population dataset, we have approached this problem by developing a semi-supervised, highly-scalable approach to select training samples from a dataset of identified commission errors. Due to the large scope this project, tens of thousands of potential samples could be derived from identified commission errors. To efficiently trim those samples down to a manageable and effective set for creating additional training sample, we statistically summarized the spectral characteristics of areas with rates of commission errors at the image tile level and grouped these tiles using affinity propagation. Highly representative members of each commission error cluster were then used to select sites for training sample creation. The model will be incrementally re-trained with the new training data to allow for an assessment of how the addition of different types of samples affects the model performance, such as precision and recall rates. By using quantitative analysis and data clustering techniques to select highly relevant training samples, we hope to improve model performance in a manner that is resource efficient, both in terms of training process

In-Situ Systematic Error Correction for Digital Volume Correlation Using a Reference Sample

KAUST Repository

Wang, B.

2017-11-27

The self-heating effect of a laboratory X-ray computed tomography (CT) scanner causes slight change in its imaging geometry, which induces translation and dilatation (i.e., artificial displacement and strain) in reconstructed volume images recorded at different times. To realize high-accuracy internal full-field deformation measurements using digital volume correlation (DVC), these artificial displacements and strains associated with unstable CT imaging must be eliminated. In this work, an effective and easily implemented reference sample compensation (RSC) method is proposed for in-situ systematic error correction in DVC. The proposed method utilizes a stationary reference sample, which is placed beside the test sample to record the artificial displacement fields caused by the self-heating effect of CT scanners. The detected displacement fields are then fitted by a parametric polynomial model, which is used to remove the unwanted artificial deformations in the test sample. Rescan tests of a stationary sample and real uniaxial compression tests performed on copper foam specimens demonstrate the accuracy, efficacy, and practicality of the presented RSC method.

In-Situ Systematic Error Correction for Digital Volume Correlation Using a Reference Sample

KAUST Repository

Wang, B.; Pan, B.; Lubineau, Gilles

2017-01-01

The self-heating effect of a laboratory X-ray computed tomography (CT) scanner causes slight change in its imaging geometry, which induces translation and dilatation (i.e., artificial displacement and strain) in reconstructed volume images recorded at different times. To realize high-accuracy internal full-field deformation measurements using digital volume correlation (DVC), these artificial displacements and strains associated with unstable CT imaging must be eliminated. In this work, an effective and easily implemented reference sample compensation (RSC) method is proposed for in-situ systematic error correction in DVC. The proposed method utilizes a stationary reference sample, which is placed beside the test sample to record the artificial displacement fields caused by the self-heating effect of CT scanners. The detected displacement fields are then fitted by a parametric polynomial model, which is used to remove the unwanted artificial deformations in the test sample. Rescan tests of a stationary sample and real uniaxial compression tests performed on copper foam specimens demonstrate the accuracy, efficacy, and practicality of the presented RSC method.

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

Science.gov (United States)

Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

2014-09-09

Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

Propagation of errors from a null balance terahertz reflectometer to a sample's relative water content

International Nuclear Information System (INIS)

Hadjiloucas, S; Walker, G C; Bowen, J W; Zafiropoulos, A

2009-01-01

The THz water content index of a sample is defined and advantages in using such metric in estimating a sample's relative water content are discussed. The errors from reflectance measurements performed at two different THz frequencies using a quasi-optical null-balance reflectometer are propagated to the errors in estimating the sample water content index.

An analytical examination of distortions in power spectra due to sampling errors

International Nuclear Information System (INIS)

Njau, E.C.

1982-06-01

Distortions introduced into spectral energy densities of sinusoid signals as well as those of more complex signals through different forms of errors in signal sampling are developed and shown analytically. The approach we have adopted in doing this involves, firstly, developing for each type of signal and for the corresponding form of sampling errors an analytical expression that gives the faulty digitization process involved in terms of the features of the particular signal. Secondly, we take advantage of a method described elsewhere [IC/82/44] to relate, as much as possible, the true spectral energy density of the signal and the corresponding spectral energy density of the faulty digitization process. Thirdly, we then develop expressions which reveal the distortions that are formed in the directly computed spectral energy density of the digitized signal. It is evident from the formulations developed herein that the types of sampling errors taken into consideration may create false peaks and other distortions that are of non-negligible concern in computed power spectra. (author)

Perceived Effects of Prevalent Errors in Contract Documents on Construction Projects

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Oluwaseun Sunday Dosumu

2018-03-01

Full Text Available One of the highly rated causes of poor performance is errors in contract documents. The objectives of this study are to investigate the prevalent errors in contract documents and their effects on construction projects. Questionnaire survey and 51 case study projects (mixed method were adopted for the study. The study also involved the use of Delphi technique to extract the possible errors that may be contained in contract documents; it did not however constitute the empirical data for the study. The sample of the study consists of 985 consulting and 275 contracting firms that engaged in the construction of building projects that were completed between 2013 and 2016 and were above the ground floor. The two-stage stratified random sampling technique was adopted for the study. The data for the study were analysed with descriptive and inferential statistics (based on Shapiro-Wilk’s test. The results of the study indicate that errors in contract documents were moderately prevalent. However, overmeasurement in bill of quantities was prevalent in private, institutional and management procured projects. Traditionally procured projects contain 68% of the errors in contract documents among the procurement methods. Drawings contain the highest number of errors, followed by bill of quantities and specifications. The severe effects of errors in contract documents were structural collapse, deterioration of buildings and contractors’ claims among others. The result of the study implies that, management procurement method is the route to error minimization in developing countries, but it may need to be backed by law and guarded against overmeasurement.

GY SAMPLING THEORY IN ENVIRONMENTAL STUDIES 2: SUBSAMPLING ERROR MEASUREMENTS

Science.gov (United States)

Sampling can be a significant source of error in the measurement process. The characterization and cleanup of hazardous waste sites require data that meet site-specific levels of acceptable quality if scientifically supportable decisions are to be made. In support of this effort,...

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

Science.gov (United States)

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

An Investigation of effective factors on nurses\\' speech errors

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Maryam Tafaroji yeganeh

2017-03-01

Full Text Available Background : Speech errors are a branch of psycholinguistic science. Speech error or slip of tongue is a natural process that happens to everyone. The importance of this research is because of sensitivity and importance of nursing in which the speech errors may be interfere in the treatment of patients, but unfortunately no research has been done yet in this field.This research has been done to study the factors (personality, stress, fatigue and insomnia which cause speech errors happen to nurses of Ilam province. Materials and Methods: The sample of this correlation-descriptive research consists of 50 nurses working in Mustafa Khomeini Hospital of Ilam province who were selected randomly. Our data were collected using The Minnesota Multiphasic Personality Inventory, NEO-Five Factor Inventory and Expanded Nursing Stress Scale, and were analyzed using SPSS version 20, descriptive, inferential and multivariate linear regression or two-variable statistical methods (with significant level: p≤0. 05. Results: 30 (60% of nurses participating in the study were female and 19 (38% were male. In this study, all three factors (type of personality, stress and fatigue have significant effects on nurses' speech errors Conclusion: 30 (60% of nurses participating in the study were female and 19 (38% were male. In this study, all three factors (type of personality, stress and fatigue have significant effects on nurses' speech errors.

Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems.

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Bhadra, Anindya; Carroll, Raymond J

2016-07-01

In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis-Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.

Statistical errors in Monte Carlo estimates of systematic errors

Energy Technology Data Exchange (ETDEWEB)

Roe, Byron P. [Department of Physics, University of Michigan, Ann Arbor, MI 48109 (United States)]. E-mail: byronroe@umich.edu

2007-01-01

For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k{sup 2}.

Statistical errors in Monte Carlo estimates of systematic errors

International Nuclear Information System (INIS)

Roe, Byron P.

2007-01-01

For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k 2

Maximum inflation of the type 1 error rate when sample size and allocation rate are adapted in a pre-planned interim look.

Science.gov (United States)

Graf, Alexandra C; Bauer, Peter

2011-06-30

We calculate the maximum type 1 error rate of the pre-planned conventional fixed sample size test for comparing the means of independent normal distributions (with common known variance) which can be yielded when sample size and allocation rate to the treatment arms can be modified in an interim analysis. Thereby it is assumed that the experimenter fully exploits knowledge of the unblinded interim estimates of the treatment effects in order to maximize the conditional type 1 error rate. The 'worst-case' strategies require knowledge of the unknown common treatment effect under the null hypothesis. Although this is a rather hypothetical scenario it may be approached in practice when using a standard control treatment for which precise estimates are available from historical data. The maximum inflation of the type 1 error rate is substantially larger than derived by Proschan and Hunsberger (Biometrics 1995; 51:1315-1324) for design modifications applying balanced samples before and after the interim analysis. Corresponding upper limits for the maximum type 1 error rate are calculated for a number of situations arising from practical considerations (e.g. restricting the maximum sample size, not allowing sample size to decrease, allowing only increase in the sample size in the experimental treatment). The application is discussed for a motivating example. Copyright © 2011 John Wiley & Sons, Ltd.

Sample positioning effects in x-ray spectrometry

International Nuclear Information System (INIS)

Carpenter, D.

Instrument error due to variation in sample position in a crystal x-ray spectrometer can easily exceed the total instrumental error. Lack of reproducibility in sample position in the x-ray optics is the single largest source of system error. The factors that account for sample positioning error are described, and many of the details of flat crystal x-ray optics are discussed

Sample size re-assessment leading to a raised sample size does not inflate type I error rate under mild conditions.

Science.gov (United States)

Broberg, Per

2013-07-19

One major concern with adaptive designs, such as the sample size adjustable designs, has been the fear of inflating the type I error rate. In (Stat Med 23:1023-1038, 2004) it is however proven that when observations follow a normal distribution and the interim result show promise, meaning that the conditional power exceeds 50%, type I error rate is protected. This bound and the distributional assumptions may seem to impose undesirable restrictions on the use of these designs. In (Stat Med 30:3267-3284, 2011) the possibility of going below 50% is explored and a region that permits an increased sample size without inflation is defined in terms of the conditional power at the interim. A criterion which is implicit in (Stat Med 30:3267-3284, 2011) is derived by elementary methods and expressed in terms of the test statistic at the interim to simplify practical use. Mathematical and computational details concerning this criterion are exhibited. Under very general conditions the type I error rate is preserved under sample size adjustable schemes that permit a raise. The main result states that for normally distributed observations raising the sample size when the result looks promising, where the definition of promising depends on the amount of knowledge gathered so far, guarantees the protection of the type I error rate. Also, in the many situations where the test statistic approximately follows a normal law, the deviation from the main result remains negligible. This article provides details regarding the Weibull and binomial distributions and indicates how one may approach these distributions within the current setting. There is thus reason to consider such designs more often, since they offer a means of adjusting an important design feature at little or no cost in terms of error rate.

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications.

Directory of Open Access Journals (Sweden)

Hugues Santin-Janin

Full Text Available BACKGROUND: Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal with respect to extrinsic factors (the Moran effect in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. METHODOLOGY/PRINCIPAL FINDINGS: The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i has been previously estimated, and (ii has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. CONCLUSION/SIGNIFICANCE: The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for

Error baseline rates of five sample preparation methods used to characterize RNA virus populations.

Directory of Open Access Journals (Sweden)

Jeffrey R Kugelman

Full Text Available Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant genomes may gain evolutionary selective advantages and give rise to dominant subpopulations, possibly even leading to the emergence of viruses resistant to medical countermeasures. Reverse transcription of virus genome populations followed by next-generation sequencing is the only available method to characterize variation for RNA viruses. However, both steps may lead to the introduction of artificial mutations, thereby skewing the data. To better understand how such errors are introduced during sample preparation, we determined and compared error baseline rates of five different sample preparation methods by analyzing in vitro transcribed Ebola virus RNA from an artificial plasmid-based system. These methods included: shotgun sequencing from plasmid DNA or in vitro transcribed RNA as a basic "no amplification" method, amplicon sequencing from the plasmid DNA or in vitro transcribed RNA as a "targeted" amplification method, sequence-independent single-primer amplification (SISPA as a "random" amplification method, rolling circle reverse transcription sequencing (CirSeq as an advanced "no amplification" method, and Illumina TruSeq RNA Access as a "targeted" enrichment method. The measured error frequencies indicate that RNA Access offers the best tradeoff between sensitivity and sample preparation error (1.4-5 of all compared methods.

Error baseline rates of five sample preparation methods used to characterize RNA virus populations

Science.gov (United States)

Kugelman, Jeffrey R.; Wiley, Michael R.; Nagle, Elyse R.; Reyes, Daniel; Pfeffer, Brad P.; Kuhn, Jens H.; Sanchez-Lockhart, Mariano; Palacios, Gustavo F.

2017-01-01

Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant genomes may gain evolutionary selective advantages and give rise to dominant subpopulations, possibly even leading to the emergence of viruses resistant to medical countermeasures. Reverse transcription of virus genome populations followed by next-generation sequencing is the only available method to characterize variation for RNA viruses. However, both steps may lead to the introduction of artificial mutations, thereby skewing the data. To better understand how such errors are introduced during sample preparation, we determined and compared error baseline rates of five different sample preparation methods by analyzing in vitro transcribed Ebola virus RNA from an artificial plasmid-based system. These methods included: shotgun sequencing from plasmid DNA or in vitro transcribed RNA as a basic “no amplification” method, amplicon sequencing from the plasmid DNA or in vitro transcribed RNA as a “targeted” amplification method, sequence-independent single-primer amplification (SISPA) as a “random” amplification method, rolling circle reverse transcription sequencing (CirSeq) as an advanced “no amplification” method, and Illumina TruSeq RNA Access as a “targeted” enrichment method. The measured error frequencies indicate that RNA Access offers the best tradeoff between sensitivity and sample preparation error (1.4−5) of all compared methods. PMID:28182717

Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications.

Science.gov (United States)

Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz

2014-07-01

Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Statistical errors in Monte Carlo estimates of systematic errors

Science.gov (United States)

Roe, Byron P.

2007-01-01

For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k2. The specific terms unisim and multisim were coined by Peter Meyers and Steve Brice, respectively, for the MiniBooNE experiment. However, the concepts have been developed over time and have been in general use for some time.

[Modal failure analysis and effects in the detection of errors in the transport of samples to the clinical laboratory].

Science.gov (United States)

Parés-Pollán, L; Gonzalez-Quintana, A; Docampo-Cordeiro, J; Vargas-Gallego, C; García-Álvarez, G; Ramos-Rodríguez, V; Diaz Rubio-García, M P

2014-01-01

Owing to the decrease in values of biochemical glucose parameter in some samples from external extraction centres, and the risk this implies to patient safety; it was decided to apply an adaptation of the «Health Services Failure Mode and Effects Analysis» (HFMEA) to manage risk during the pre-analytical phase of sample transportation from external centres to clinical laboratories. A retrospective study of glucose parameter was conducted during two consecutive months. The analysis was performed in its different phases: to define the HFMEA topic, assemble the team, graphically describe the process, conduct a hazard analysis, design the intervention and indicators, and identify a person to be responsible for ensuring completion of each action. The results of glucose parameter in one of the transport routes, were significantly lower (P=.006). The errors and potential causes of this problem were analysed, and criteria of criticality and detectability were applied (score≥8) in the decision tree. It was decided to: develop a document management system; reorganise extractions and transport routes in some centres; quality control of the sample container ice-packs, and the time and temperature during transportation. This work proposes quality indicators for controlling time and temperature of transported samples in the pre-analytical phase. Periodic review of certain laboratory parameters can help to detect problems in transporting samples. The HFMEA technique is useful for the clinical laboratory. Copyright © 2013 SECA. Published by Elsevier Espana. All rights reserved.

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

Science.gov (United States)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Droplet Size-Aware and Error-Correcting Sample Preparation Using Micro-Electrode-Dot-Array Digital Microfluidic Biochips.

Science.gov (United States)

Li, Zipeng; Lai, Kelvin Yi-Tse; Chakrabarty, Krishnendu; Ho, Tsung-Yi; Lee, Chen-Yi

2017-12-01

Sample preparation in digital microfluidics refers to the generation of droplets with target concentrations for on-chip biochemical applications. In recent years, digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation. However, there remain two major problems associated with sample preparation on a conventional DMFB. First, only a (1:1) mixing/splitting model can be used, leading to an increase in the number of fluidic operations required for sample preparation. Second, only a limited number of sensors can be integrated on a conventional DMFB; as a result, the latency for error detection during sample preparation is significant. To overcome these drawbacks, we adopt a next generation DMFB platform, referred to as micro-electrode-dot-array (MEDA), for sample preparation. We propose the first sample-preparation method that exploits the MEDA-specific advantages of fine-grained control of droplet sizes and real-time droplet sensing. Experimental demonstration using a fabricated MEDA biochip and simulation results highlight the effectiveness of the proposed sample-preparation method.

Seeing your error alters my pointing: observing systematic pointing errors induces sensori-motor after-effects.

Directory of Open Access Journals (Sweden)

Roberta Ronchi

Full Text Available During the procedure of prism adaptation, subjects execute pointing movements to visual targets under a lateral optical displacement: as consequence of the discrepancy between visual and proprioceptive inputs, their visuo-motor activity is characterized by pointing errors. The perception of such final errors triggers error-correction processes that eventually result into sensori-motor compensation, opposite to the prismatic displacement (i.e., after-effects. Here we tested whether the mere observation of erroneous pointing movements, similar to those executed during prism adaptation, is sufficient to produce adaptation-like after-effects. Neurotypical participants observed, from a first-person perspective, the examiner's arm making incorrect pointing movements that systematically overshot visual targets location to the right, thus simulating a rightward optical deviation. Three classical after-effect measures (proprioceptive, visual and visual-proprioceptive shift were recorded before and after first-person's perspective observation of pointing errors. Results showed that mere visual exposure to an arm that systematically points on the right-side of a target (i.e., without error correction produces a leftward after-effect, which mostly affects the observer's proprioceptive estimation of her body midline. In addition, being exposed to such a constant visual error induced in the observer the illusion "to feel" the seen movement. These findings indicate that it is possible to elicit sensori-motor after-effects by mere observation of movement errors.

Distribution of the Determinant of the Sample Correlation Matrix: Monte Carlo Type One Error Rates.

Science.gov (United States)

Reddon, John R.; And Others

1985-01-01

Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)

Errors in causal inference: an organizational schema for systematic error and random error.

Science.gov (United States)

Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji

2016-11-01

To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.

Climatologies from satellite measurements: the impact of orbital sampling on the standard error of the mean

Directory of Open Access Journals (Sweden)

M. Toohey

2013-04-01

Full Text Available Climatologies of atmospheric observations are often produced by binning measurements according to latitude and calculating zonal means. The uncertainty in these climatological means is characterised by the standard error of the mean (SEM. However, the usual estimator of the SEM, i.e., the sample standard deviation divided by the square root of the sample size, holds only for uncorrelated randomly sampled measurements. Measurements of the atmospheric state along a satellite orbit cannot always be considered as independent because (a the time-space interval between two nearest observations is often smaller than the typical scale of variations in the atmospheric state, and (b the regular time-space sampling pattern of a satellite instrument strongly deviates from random sampling. We have developed a numerical experiment where global chemical fields from a chemistry climate model are sampled according to real sampling patterns of satellite-borne instruments. As case studies, the model fields are sampled using sampling patterns of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS and Atmospheric Chemistry Experiment Fourier-Transform Spectrometer (ACE-FTS satellite instruments. Through an iterative subsampling technique, and by incorporating information on the random errors of the MIPAS and ACE-FTS measurements, we produce empirical estimates of the standard error of monthly mean zonal mean model O3 in 5° latitude bins. We find that generally the classic SEM estimator is a conservative estimate of the SEM, i.e., the empirical SEM is often less than or approximately equal to the classic estimate. Exceptions occur only when natural variability is larger than the random measurement error, and specifically in instances where the zonal sampling distribution shows non-uniformity with a similar zonal structure as variations in the sampled field, leading to maximum sensitivity to arbitrary phase shifts between the sample distribution and

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

Science.gov (United States)

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

Sequential effects in pigeon delayed matching-to-sample performance.

Science.gov (United States)

Roitblat, H L; Scopatz, R A

1983-04-01

Pigeons were tested in a three-alternative delayed matching-to-sample task in which second-choices were permitted following first-choice errors. Sequences of responses both within and between trials were examined in three experiments. The first experiment demonstrates that the sample information contained in first-choice errors is not sufficient to account for the observed pattern of second choices. This result implies that second-choices following first-choice errors are based on a second examination of the contents of working memory. Proactive interference was found in the second experiment in the form of a dependency, beyond that expected on the basis of trial independent response bias, of first-choices from one trial on the first-choice emitted on the previous trial. Samples from the previous trial were not found to exert a significant influence on later trials. The magnitude of the intertrial association (Experiment 3) did not depend on the duration of the intertrial interval. In contrast, longer intertrial intervals and longer sample durations did facilitate choice accuracy, by strengthening the association between current samples and choices. These results are incompatible with a trace-decay and competition model; they suggest strongly that multiple influences act simultaneously and independently to control delayed matching-to-sample responding. These multiple influences include memory for the choice occurring on the previous trial, memory for the sample, and general effects of trial spacing.

Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots.

Science.gov (United States)

Župunski, Vesna; Jevtić, Radivoje; Jokić, Vesna Spasić; Župunski, Ljubica; Lalošević, Mirjana; Ćirić, Mihajlo; Ćurčić, Živko

2017-06-01

Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m 2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of soil. Goodness of fit of data to probability distribution tested with χ 2 test confirmed a negative binomial distribution of cyst counts for 21 out of 23 plots. The recommended measure of sampling precision of 17% expressed through coefficient of variation ( cv ) was achieved if the plots of 1 m 2 contaminated with more than 90 cysts per 100 g of soil were sampled with 10-core bulk samples taken in five repetitions. If plots were contaminated with less than 75 cysts per 100 g of soil, 10-core bulk samples taken in seven repetitions gave cv higher than 23%. This study indicates that more attention should be paid on estimation of sampling error in experimental field plots to ensure more reliable estimation of population density of cyst nematodes.

Over-Sampling Codebook-Based Hybrid Minimum Sum-Mean-Square-Error Precoding for Millimeter-Wave 3D-MIMO

KAUST Repository

Mao, Jiening

2018-05-23

Abstract: Hybrid precoding design is challenging for millimeter-wave (mmWave) massive MIMO. Most prior hybrid precoding schemes are designed to maximize the sum spectral efficiency (SSE), while seldom investigate the bit-error-rate (BER). Therefore, this letter designs an over-sampling codebook (OSC)-based hybrid minimum sum-mean-square-error (min-SMSE) precoding to optimize the BER. Specifically, given the effective baseband channel consisting of the real channel and analog precoding, we first design the digital precoder/combiner based on min-SMSE criterion to optimize the BER. To further reduce the SMSE between the transmit and receive signals, we propose an OSC-based joint analog precoder/combiner (JAPC) design. Simulation results show that the proposed scheme can achieve the better performance than its conventional counterparts.

Over-Sampling Codebook-Based Hybrid Minimum Sum-Mean-Square-Error Precoding for Millimeter-Wave 3D-MIMO

KAUST Repository

Mao, Jiening; Gao, Zhen; Wu, Yongpeng; Alouini, Mohamed-Slim

2018-01-01

Hybrid precoding design is challenging for millimeter-wave (mmWave) massive MIMO. Most prior hybrid precoding schemes are designed to maximize the sum spectral efficiency (SSE), while seldom investigate the bit-error-rate (BER). Therefore, this letter designs an over-sampling codebook (OSC)-based hybrid minimum sum-mean-square-error (min-SMSE) precoding to optimize the BER. Specifically, given the effective baseband channel consisting of the real channel and analog precoding, we first design the digital precoder/combiner based on min-SMSE criterion to optimize the BER. To further reduce the SMSE between the transmit and receive signals, we propose an OSC-based joint analog precoder/combiner (JAPC) design. Simulation results show that the proposed scheme can achieve the better performance than its conventional counterparts.

Effects of sterilization treatments on the analysis of TOC in water samples.

Science.gov (United States)

Shi, Yiming; Xu, Lingfeng; Gong, Dongqin; Lu, Jun

2010-01-01

Decomposition experiments conducted with and without microbial processes are commonly used to study the effects of environmental microorganisms on the degradation of organic pollutants. However, the effects of biological pretreatment (sterilization) on organic matter often have a negative impact on such experiments. Based on the principle of water total organic carbon (TOC) analysis, the effects of physical sterilization treatments on determination of TOC and other water quality parameters were investigated. The results revealed that two conventional physical sterilization treatments, autoclaving and 60Co gamma-radiation sterilization, led to the direct decomposition of some organic pollutants, resulting in remarkable errors in the analysis of TOC in water samples. Furthermore, the extent of the errors varied with the intensity and the duration of sterilization treatments. Accordingly, a novel sterilization method for water samples, 0.45 microm micro-filtration coupled with ultraviolet radiation (MCUR), was developed in the present study. The results indicated that the MCUR method was capable of exerting a high bactericidal effect on the water sample while significantly decreasing the negative impact on the analysis of TOC and other water quality parameters. Before and after sterilization treatments, the relative errors of TOC determination could be controlled to lower than 3% for water samples with different categories and concentrations of organic pollutants by using MCUR.

Optical Waveform Sampling and Error-Free Demultiplexing of 1.28 Tb/s Serial Data in a Nanoengineered Silicon Waveguide

DEFF Research Database (Denmark)

Ji, Hua; Pu, Minhao; Hu, Hao

2011-01-01

This paper presents the experimental demonstrations of using a pure nanoengineered silicon waveguide for 1.28 Tb/s serial data optical waveform sampling and 1.28 Tb/s–10 Gb/s error free demultiplexing. The 330-fs pulses are resolved in each 780-fs time slot in waveform sampling. Error...

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error

OpenAIRE

Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M

2014-01-01

Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectom...

Outlier removal, sum scores, and the inflation of the Type I error rate in independent samples t tests: the power of alternatives and recommendations.

Science.gov (United States)

Bakker, Marjan; Wicherts, Jelte M

2014-09-01

In psychology, outliers are often excluded before running an independent samples t test, and data are often nonnormal because of the use of sum scores based on tests and questionnaires. This article concerns the handling of outliers in the context of independent samples t tests applied to nonnormal sum scores. After reviewing common practice, we present results of simulations of artificial and actual psychological data, which show that the removal of outliers based on commonly used Z value thresholds severely increases the Type I error rate. We found Type I error rates of above 20% after removing outliers with a threshold value of Z = 2 in a short and difficult test. Inflations of Type I error rates are particularly severe when researchers are given the freedom to alter threshold values of Z after having seen the effects thereof on outcomes. We recommend the use of nonparametric Mann-Whitney-Wilcoxon tests or robust Yuen-Welch tests without removing outliers. These alternatives to independent samples t tests are found to have nominal Type I error rates with a minimal loss of power when no outliers are present in the data and to have nominal Type I error rates and good power when outliers are present. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Refractive Error in a Sample of Black High School Children in South Africa.

Science.gov (United States)

Wajuihian, Samuel Otabor; Hansraj, Rekha

2017-12-01

This study focused on a cohort that has not been studied and who currently have limited access to eye care services. The findings, while improving the understanding of the distribution of refractive errors, also enabled identification of children requiring intervention and provided a guide for future resource allocation. The aim of conducting the study was to determine the prevalence and distribution of refractive error and its association with gender, age, and school grade level. Using a multistage random cluster sampling, 1586 children, 632 males (40%) and 954 females (60%), were selected. Their ages ranged between 13 and 18 years with a mean of 15.81 ± 1.56 years. The visual functions evaluated included visual acuity using the logarithm of minimum angle of resolution chart and refractive error measured using the autorefractor and then refined subjectively. Axis astigmatism was presented in the vector method where positive values of J0 indicated with-the-rule astigmatism, negative values indicated against-the-rule astigmatism, whereas J45 represented oblique astigmatism. Overall, patients were myopic with a mean spherical power for right eye of -0.02 ± 0.47; mean astigmatic cylinder power was -0.09 ± 0.27 with mainly with-the-rule astigmatism (J0 = 0.01 ± 0.11). The prevalence estimates were as follows: myopia (at least -0.50) 7% (95% confidence interval [CI], 6 to 9%), hyperopia (at least 0.5) 5% (95% CI, 4 to 6%), astigmatism (at least -0.75 cylinder) 3% (95% CI, 2 to 4%), and anisometropia 3% (95% CI, 2 to 4%). There was no significant association between refractive error and any of the categories (gender, age, and grade levels). The prevalence of refractive error in the sample of high school children was relatively low. Myopia was the most prevalent, and findings on its association with age suggest that the prevalence of myopia may be stabilizing at late teenage years.

Competition increases binding errors in visual working memory.

Science.gov (United States)

Emrich, Stephen M; Ferber, Susanne

2012-04-20

When faced with maintaining multiple objects in visual working memory, item information must be bound to the correct object in order to be correctly recalled. Sometimes, however, binding errors occur, and participants report the feature (e.g., color) of an unprobed, non-target item. In the present study, we examine whether the configuration of sample stimuli affects the proportion of these binding errors. The results demonstrate that participants mistakenly report the identity of the unprobed item (i.e., they make a non-target response) when sample items are presented close together in space, suggesting that binding errors can increase independent of increases in memory load. Moreover, the proportion of these non-target responses is linearly related to the distance between sample items, suggesting that these errors are spatially specific. Finally, presenting sample items sequentially decreases non-target responses, suggesting that reducing competition between sample stimuli reduces the number of binding errors. Importantly, these effects all occurred without increases in the amount of error in the memory representation. These results suggest that competition during encoding can account for some of the binding errors made during VWM recall.

Negative Input for Grammatical Errors: Effects after a Lag of 12 Weeks

Science.gov (United States)

Saxton, Matthew; Backley, Phillip; Gallaway, Clare

2005-01-01

Effects of negative input for 13 categories of grammatical error were assessed in a longitudinal study of naturalistic adult-child discourse. Two-hour samples of conversational interaction were obtained at two points in time, separated by a lag of 12 weeks, for 12 children (mean age 2;0 at the start). The data were interpreted within the framework…

Optimization of sample absorbance for quantitative analysis in the presence of pathlength error in the IR and NIR regions

International Nuclear Information System (INIS)

Hirschfeld, T.; Honigs, D.; Hieftje, G.

1985-01-01

Optical absorbance levels for quantiative analysis in the presence of photometric error have been described in the past. In newer instrumentation, such as FT-IR and NIRA spectrometers, the photometric error is no longer limiting. In these instruments, pathlength error due to cell or sampling irreproducibility is often a major concern. One can derive optimal absorbance by taking both pathlength and photometric errors into account. This paper analyzes the cases of pathlength error >> photometric error (trivial) and various cases in which the pathlength errors and the photometric error are of the same order: adjustable concentration (trivial until dilution errors are considered), constant relative pathlength error (trivial), and constant absolute pathlength error. The latter, in particular, is analyzed in detail to give the behavior of the error, the behavior of the optimal absorbance in its presence, and the total error levels attainable

Error framing effects on performance: cognitive, motivational, and affective pathways.

Science.gov (United States)

Steele-Johnson, Debra; Kalinoski, Zachary T

2014-01-01

Our purpose was to examine whether positive error framing, that is, making errors salient and cuing individuals to see errors as useful, can benefit learning when task exploration is constrained. Recent research has demonstrated the benefits of a newer approach to training, that is, error management training, that includes the opportunity to actively explore the task and framing errors as beneficial to learning complex tasks (Keith & Frese, 2008). Other research has highlighted the important role of errors in on-the-job learning in complex domains (Hutchins, 1995). Participants (N = 168) from a large undergraduate university performed a class scheduling task. Results provided support for a hypothesized path model in which error framing influenced cognitive, motivational, and affective factors which in turn differentially affected performance quantity and quality. Within this model, error framing had significant direct effects on metacognition and self-efficacy. Our results suggest that positive error framing can have beneficial effects even when tasks cannot be structured to support extensive exploration. Whereas future research can expand our understanding of error framing effects on outcomes, results from the current study suggest that positive error framing can facilitate learning from errors in real-time performance of tasks.

The effect of errors in charged particle beams

International Nuclear Information System (INIS)

Carey, D.C.

1987-01-01

Residual errors in a charged particle optical system determine how well the performance of the system conforms to the theory on which it is based. Mathematically possible optical modes can sometimes be eliminated as requiring precisions not attainable. Other plans may require introduction of means of correction for the occurrence of various errors. Error types include misalignments, magnet fabrication precision limitations, and magnet current regulation errors. A thorough analysis of a beam optical system requires computer simulation of all these effects. A unified scheme for the simulation of errors and their correction is discussed

Power and sample size calculations in the presence of phenotype errors for case/control genetic association studies

Directory of Open Access Journals (Sweden)

Finch Stephen J

2005-04-01

Full Text Available Abstract Background Phenotype error causes reduction in power to detect genetic association. We present a quantification of phenotype error, also known as diagnostic error, on power and sample size calculations for case-control genetic association studies between a marker locus and a disease phenotype. We consider the classic Pearson chi-square test for independence as our test of genetic association. To determine asymptotic power analytically, we compute the distribution's non-centrality parameter, which is a function of the case and control sample sizes, genotype frequencies, disease prevalence, and phenotype misclassification probabilities. We derive the non-centrality parameter in the presence of phenotype errors and equivalent formulas for misclassification cost (the percentage increase in minimum sample size needed to maintain constant asymptotic power at a fixed significance level for each percentage increase in a given misclassification parameter. We use a linear Taylor Series approximation for the cost of phenotype misclassification to determine lower bounds for the relative costs of misclassifying a true affected (respectively, unaffected as a control (respectively, case. Power is verified by computer simulation. Results Our major findings are that: (i the median absolute difference between analytic power with our method and simulation power was 0.001 and the absolute difference was no larger than 0.011; (ii as the disease prevalence approaches 0, the cost of misclassifying a unaffected as a case becomes infinitely large while the cost of misclassifying an affected as a control approaches 0. Conclusion Our work enables researchers to specifically quantify power loss and minimum sample size requirements in the presence of phenotype errors, thereby allowing for more realistic study design. For most diseases of current interest, verifying that cases are correctly classified is of paramount importance.

Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies.

Science.gov (United States)

Goldman, Gretchen T; Mulholland, James A; Russell, Armistead G; Strickland, Matthew J; Klein, Mitchel; Waller, Lance A; Tolbert, Paige E

2011-06-22

Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.e. additive on the log scale) and model it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range (IQR) basis in a time-series study in Atlanta. Daily measures of twelve ambient air pollutants were analyzed: NO2, NOx, O3, SO2, CO, PM10 mass, PM2.5 mass, and PM2.5 components sulfate, nitrate, ammonium, elemental carbon and organic carbon. Semivariogram analysis was applied to assess spatial variability. Error due to this spatial variability was added to a reference pollutant time-series on the log scale using Monte Carlo simulations. Each of these time-series was exponentiated and introduced to a Poisson generalized linear model of cardiovascular disease emergency department visits. Measurement error resulted in reduced statistical significance for the risk ratio estimates for all amounts (corresponding to different pollutants) and types of error. When modelled as classical-type error, risk ratios were attenuated, particularly for primary air pollutants, with average attenuation in risk ratios on a per unit of measurement basis ranging from 18% to 92% and on an IQR basis ranging from 18% to 86%. When modelled as Berkson-type error, risk ratios per unit of measurement were biased away from the null hypothesis by 2% to 31%, whereas risk ratios per IQR were attenuated (i.e. biased toward the null) by 5% to 34%. For CO modelled error amount, a range of error types were simulated and effects on risk ratio bias and significance were observed. For multiplicative error, both the amount and type of measurement error impact health effect estimates in air pollution epidemiology. By modelling

Evaluation of errors for mass-spectrometric analysis with surface-ionization type mass-spectrometer (statistical evaluation of mass-discrimination effect)

International Nuclear Information System (INIS)

Wada, Y.

1981-01-01

The surface-ionization type mass-spectrometer is widely used as an apparatus for quality assurance, accountability and safeguarding of nuclear materials, and for this analysis it has become an important factor to statistically evaluate an analytical error which consists of a random error and a systematic error. The major factor of this systematic error was the mass-discrimination effect. In this paper, various assays for evaluating the factor of variation on the mass-discrimination effect were studied and the data obtained were statistically evaluated. As a result of these analyses, it was proved that the factor of variation on the mass-discrimination effect was not attributed to the acid concentration of sample, sample size on the filament and supplied voltage for a multiplier, but mainly to the filament temperature during the mass-spectrometric analysis. The mass-discrimination effect values β which were usually calculated from the measured data of uranium, plutonium or boron isotopic standard sample were not so significant dependently of the difference of U-235, Pu-239 or B-10 isotopic abundance. Furthermore, in the case of U and Pu, measurement conditions and the mass range of these isotopes were almost similar, and these values β were not statistically significant between U and Pu. On the other hand, the value β for boron was about a third of the value β for U or Pu, but compared with the coefficient of the correction on the mass-discrimination effect for the difference of mass-number, ΔM, these coefficient values were almost the same among U, Pu, and B.As for the isotopic analysis error of U, Pu, Nd and B, it was proved that the isotopic abundance of these elements and the isotopic analysis error were in a relationship of quadratic curves on a logarithmic-logarithmic scale

On the errors on Omega(0): Monte Carlo simulations of the EMSS cluster sample

DEFF Research Database (Denmark)

Oukbir, J.; Arnaud, M.

2001-01-01

We perform Monte Carlo simulations of synthetic EMSS cluster samples, to quantify the systematic errors and the statistical uncertainties on the estimate of Omega (0) derived from fits to the cluster number density evolution and to the X-ray temperature distribution up to z=0.83. We identify...... the scatter around the relation between cluster X-ray luminosity and temperature to be a source of systematic error, of the order of Delta (syst)Omega (0) = 0.09, if not properly taken into account in the modelling. After correcting for this bias, our best Omega (0) is 0.66. The uncertainties on the shape...

Sample Size Bounding and Context Ranking as Approaches to the Human Error Quantification Problem

Energy Technology Data Exchange (ETDEWEB)

Reer, B

2004-03-01

The paper describes a technique denoted as Sub-Sample-Size Bounding (SSSB), which is useable for the statistical derivation of context-specific probabilities from data available in existing reports on operating experience. Applications to human reliability analysis (HRA) are emphasised in the presentation of this technique. Exemplified by a sample of 180 abnormal event sequences, the manner in which SSSB can provide viable input for the quantification of errors of commission (EOCs) are outlined. (author)

Sample Size Bounding and Context Ranking as Approaches to the Human Error Quantification Problem

International Nuclear Information System (INIS)

Reer, B.

2004-01-01

The paper describes a technique denoted as Sub-Sample-Size Bounding (SSSB), which is useable for the statistical derivation of context-specific probabilities from data available in existing reports on operating experience. Applications to human reliability analysis (HRA) are emphasised in the presentation of this technique. Exemplified by a sample of 180 abnormal event sequences, the manner in which SSSB can provide viable input for the quantification of errors of commission (EOCs) are outlined. (author)

Spanish exit polls. Sampling error or nonresponse bias?

Directory of Open Access Journals (Sweden)

Pavía, Jose M.

2016-09-01

Full Text Available Countless examples of misleading forecasts on behalf of both pre-election and exit polls can be found all over the world. Non-representative samples due to differential nonresponse have been claimed as being the main reason for inaccurate exit-poll projections. In real inference problems, it is seldom possible to compare estimates and true values. Electoral forecasts are an exception. Comparisons between estimates and final outcomes can be carried out once votes have been tallied. In this paper, we examine the raw data collected in seven exit polls conducted in Spain and test the likelihood that the data collected in each sampled voting location can be considered as a random sample of actual results. Knowing the answer to this is relevant for both electoral analysts and forecasters as, if the hypothesis is rejected, the shortcomings of the collected data would need amending. Analysts could improve the quality of their computations by implementing local correction strategies. We find strong evidence of nonsampling error in Spanish exit polls and evidence that the political context matters. Nonresponse bias is larger in polarized elections and in a climate of fearExiste un gran número de ejemplos de predicciones inexactas obtenidas a partir tanto de encuestas pre-electorales como de encuestas a pie de urna a lo largo del mundo. La presencia de tasas de no-respuesta diferencial entre distintos tipos de electores ha sido la principal razón esgrimida para justificar las proyecciones erróneas en las encuestas a pie de urna. En problemas de inferencia rara vez es posible comparar estimaciones y valores reales. Las predicciones electorales son una excepción. La comparación entre estimaciones y resultados finales puede realizarse una vez los votos han sido contabilizados. En este trabajo, examinamos los datos brutos recogidos en siete encuestas a pie de urna realizadas en España y testamos la hipótesis de que los datos recolectados en cada punto

Action errors, error management, and learning in organizations.

Science.gov (United States)

Frese, Michael; Keith, Nina

2015-01-03

Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.

Irregular analytical errors in diagnostic testing - a novel concept.

Science.gov (United States)

Vogeser, Michael; Seger, Christoph

2018-02-23

In laboratory medicine, routine periodic analyses for internal and external quality control measurements interpreted by statistical methods are mandatory for batch clearance. Data analysis of these process-oriented measurements allows for insight into random analytical variation and systematic calibration bias over time. However, in such a setting, any individual sample is not under individual quality control. The quality control measurements act only at the batch level. Quantitative or qualitative data derived for many effects and interferences associated with an individual diagnostic sample can compromise any analyte. It is obvious that a process for a quality-control-sample-based approach of quality assurance is not sensitive to such errors. To address the potential causes and nature of such analytical interference in individual samples more systematically, we suggest the introduction of a new term called the irregular (individual) analytical error. Practically, this term can be applied in any analytical assay that is traceable to a reference measurement system. For an individual sample an irregular analytical error is defined as an inaccuracy (which is the deviation from a reference measurement procedure result) of a test result that is so high it cannot be explained by measurement uncertainty of the utilized routine assay operating within the accepted limitations of the associated process quality control measurements. The deviation can be defined as the linear combination of the process measurement uncertainty and the method bias for the reference measurement system. Such errors should be coined irregular analytical errors of the individual sample. The measurement result is compromised either by an irregular effect associated with the individual composition (matrix) of the sample or an individual single sample associated processing error in the analytical process. Currently, the availability of reference measurement procedures is still highly limited, but LC

Learning from Errors: Effects of Teachers Training on Students' Attitudes towards and Their Individual Use of Errors

Science.gov (United States)

Rach, Stefanie; Ufer, Stefan; Heinze, Aiso

2013-01-01

Constructive error handling is considered an important factor for individual learning processes. In a quasi-experimental study with Grades 6 to 9 students, we investigate effects on students' attitudes towards errors as learning opportunities in two conditions: an error-tolerant classroom culture, and the first condition along with additional…

The Effect of Random Error on Diagnostic Accuracy Illustrated with the Anthropometric Diagnosis of Malnutrition

Science.gov (United States)

2016-01-01

Background It is often thought that random measurement error has a minor effect upon the results of an epidemiological survey. Theoretically, errors of measurement should always increase the spread of a distribution. Defining an illness by having a measurement outside an established healthy range will lead to an inflated prevalence of that condition if there are measurement errors. Methods and results A Monte Carlo simulation was conducted of anthropometric assessment of children with malnutrition. Random errors of increasing magnitude were imposed upon the populations and showed that there was an increase in the standard deviation with each of the errors that became exponentially greater with the magnitude of the error. The potential magnitude of the resulting error of reported prevalence of malnutrition were compared with published international data and found to be of sufficient magnitude to make a number of surveys and the numerous reports and analyses that used these data unreliable. Conclusions The effect of random error in public health surveys and the data upon which diagnostic cut-off points are derived to define “health” has been underestimated. Even quite modest random errors can more than double the reported prevalence of conditions such as malnutrition. Increasing sample size does not address this problem, and may even result in less accurate estimates. More attention needs to be paid to the selection, calibration and maintenance of instruments, measurer selection, training & supervision, routine estimation of the likely magnitude of errors using standardization tests, use of statistical likelihood of error to exclude data from analysis and full reporting of these procedures in order to judge the reliability of survey reports. PMID:28030627

The error analysis of coke moisture measured by neutron moisture gauge

International Nuclear Information System (INIS)

Tian Huixing

1995-01-01

The error of coke moisture measured by neutron method in the iron and steel industry is analyzed. The errors are caused by inaccurate sampling location in the calibration procedure on site. By comparison, the instrument error and the statistical fluctuation error are smaller. So the sampling proportion should be increased as large as possible in the calibration procedure on site, and a satisfied calibration effect can be obtained on a suitable size hopper

Effects of systematic sampling on satellite estimates of deforestation rates

International Nuclear Information System (INIS)

Steininger, M K; Godoy, F; Harper, G

2009-01-01

Options for satellite monitoring of deforestation rates over large areas include the use of sampling. Sampling may reduce the cost of monitoring but is also a source of error in estimates of areas and rates. A common sampling approach is systematic sampling, in which sample units of a constant size are distributed in some regular manner, such as a grid. The proposed approach for the 2010 Forest Resources Assessment (FRA) of the UN Food and Agriculture Organization (FAO) is a systematic sample of 10 km wide squares at every 1 deg. intersection of latitude and longitude. We assessed the outcome of this and other systematic samples for estimating deforestation at national, sub-national and continental levels. The study is based on digital data on deforestation patterns for the five Amazonian countries outside Brazil plus the Brazilian Amazon. We tested these schemes by varying sample-unit size and frequency. We calculated two estimates of sampling error. First we calculated the standard errors, based on the size, variance and covariance of the samples, and from this calculated the 95% confidence intervals (CI). Second, we calculated the actual errors, based on the difference between the sample-based estimates and the estimates from the full-coverage maps. At the continental level, the 1 deg., 10 km scheme had a CI of 21% and an actual error of 8%. At the national level, this scheme had CIs of 126% for Ecuador and up to 67% for other countries. At this level, increasing sampling density to every 0.25 deg. produced a CI of 32% for Ecuador and CIs of up to 25% for other countries, with only Brazil having a CI of less than 10%. Actual errors were within the limits of the CIs in all but two of the 56 cases. Actual errors were half or less of the CIs in all but eight of these cases. These results indicate that the FRA 2010 should have CIs of smaller than or close to 10% at the continental level. However, systematic sampling at the national level yields large CIs unless the

Effects of human errors on the determination of surveillance test interval

International Nuclear Information System (INIS)

Chung, Dae Wook; Koo, Bon Hyun

1990-01-01

This paper incorporates the effects of human error relevant to the periodic test on the unavailability of the safety system as well as the component unavailability. Two types of possible human error during the test are considered. One is the possibility that a good safety system is inadvertently left in a bad state after the test (Type A human error) and the other is the possibility that bad safety system is undetected upon the test (Type B human error). An event tree model is developed for the steady-state unavailability of safety system to determine the effects of human errors on the component unavailability and the test interval. We perform the reliability analysis of safety injection system (SIS) by applying aforementioned two types of human error to safety injection pumps. Results of various sensitivity analyses show that; 1) the appropriate test interval decreases and steady-state unavailability increases as the probabilities of both types of human errors increase, and they are far more sensitive to Type A human error than Type B and 2) the SIS unavailability increases slightly as the probability of Type B human error increases, and significantly as the probability of Type A human error increases. Therefore, to avoid underestimation, the effects of human error should be incorporated in the system reliability analysis which aims at the relaxations of the surveillance test intervals, and Type A human error has more important effect on the unavailability and surveillance test interval

MEASUREMENT ERROR EFFECT ON THE POWER OF CONTROL CHART FOR ZERO-TRUNCATED POISSON DISTRIBUTION

Directory of Open Access Journals (Sweden)

Ashit Chakraborty

2013-09-01

Full Text Available Measurement error is the difference between the true value and the measured value of a quantity that exists in practice and may considerably affect the performance of control charts in some cases. Measurement error variability has uncertainty which can be from several sources. In this paper, we have studied the effect of these sources of variability on the power characteristics of control chart and obtained the values of average run length (ARL for zero-truncated Poisson distribution (ZTPD. Expression of the power of control chart for variable sample size under standardized normal variate for ZTPD is also derived.

Optical waveform sampling and error-free demultiplexing of 1.28 Tbit/s serial data in a silicon nanowire

DEFF Research Database (Denmark)

Ji, Hua; Hu, Hao; Galili, Michael

2010-01-01

We experimentally demonstrate 640 Gbit/s and 1.28 Tbit/s serial data optical waveform sampling and 640-to-10 Gbit/s and 1.28 Tbit/s-to-10 Gbit/s error-free demultiplexing using four-wave mixing in a 300nm$$450nm$$5mm silicon nanowire.......We experimentally demonstrate 640 Gbit/s and 1.28 Tbit/s serial data optical waveform sampling and 640-to-10 Gbit/s and 1.28 Tbit/s-to-10 Gbit/s error-free demultiplexing using four-wave mixing in a 300nm$$450nm$$5mm silicon nanowire....

Learning from errors in super-resolution.

Science.gov (United States)

Tang, Yi; Yuan, Yuan

2014-11-01

A novel framework of learning-based super-resolution is proposed by employing the process of learning from the estimation errors. The estimation errors generated by different learning-based super-resolution algorithms are statistically shown to be sparse and uncertain. The sparsity of the estimation errors means most of estimation errors are small enough. The uncertainty of the estimation errors means the location of the pixel with larger estimation error is random. Noticing the prior information about the estimation errors, a nonlinear boosting process of learning from these estimation errors is introduced into the general framework of the learning-based super-resolution. Within the novel framework of super-resolution, a low-rank decomposition technique is used to share the information of different super-resolution estimations and to remove the sparse estimation errors from different learning algorithms or training samples. The experimental results show the effectiveness and the efficiency of the proposed framework in enhancing the performance of different learning-based algorithms.

Research on effects of phase error in phase-shifting interferometer

Science.gov (United States)

Wang, Hongjun; Wang, Zhao; Zhao, Hong; Tian, Ailing; Liu, Bingcai

2007-12-01

Referring to phase-shifting interferometry technology, the phase shifting error from the phase shifter is the main factor that directly affects the measurement accuracy of the phase shifting interferometer. In this paper, the resources and sorts of phase shifting error were introduction, and some methods to eliminate errors were mentioned. Based on the theory of phase shifting interferometry, the effects of phase shifting error were analyzed in detail. The Liquid Crystal Display (LCD) as a new shifter has advantage as that the phase shifting can be controlled digitally without any mechanical moving and rotating element. By changing coded image displayed on LCD, the phase shifting in measuring system was induced. LCD's phase modulation characteristic was analyzed in theory and tested. Based on Fourier transform, the effect model of phase error coming from LCD was established in four-step phase shifting interferometry. And the error range was obtained. In order to reduce error, a new error compensation algorithm was put forward. With this method, the error can be obtained by process interferogram. The interferogram can be compensated, and the measurement results can be obtained by four-step phase shifting interferogram. Theoretical analysis and simulation results demonstrate the feasibility of this approach to improve measurement accuracy.

Ironic Effects of Drawing Attention to Story Errors

Science.gov (United States)

Eslick, Andrea N.; Fazio, Lisa K.; Marsh, Elizabeth J.

2014-01-01

Readers learn errors embedded in fictional stories and use them to answer later general knowledge questions (Marsh, Meade, & Roediger, 2003). Suggestibility is robust and occurs even when story errors contradict well-known facts. The current study evaluated whether suggestibility is linked to participants’ inability to judge story content as correct versus incorrect. Specifically, participants read stories containing correct and misleading information about the world; some information was familiar (making error discovery possible), while some was more obscure. To improve participants’ monitoring ability, we highlighted (in red font) a subset of story phrases requiring evaluation; readers no longer needed to find factual information. Rather, they simply needed to evaluate its correctness. Readers were more likely to answer questions with story errors if they were highlighted in red font, even if they contradicted well-known facts. Though highlighting to-be-evaluated information freed cognitive resources for monitoring, an ironic effect occurred: Drawing attention to specific errors increased rather than decreased later suggestibility. Failure to monitor for errors, not failure to identify the information requiring evaluation, leads to suggestibility. PMID:21294039

Data error effects on net radiation and evapotranspiration estimation

International Nuclear Information System (INIS)

Llasat, M.C.; Snyder, R.L.

1998-01-01

The objective of this paper is to evaluate the potential error in estimating the net radiation and reference evapotranspiration resulting from errors in the measurement or estimation of weather parameters. A methodology for estimating the net radiation using hourly weather variables measured at a typical agrometeorological station (e.g., solar radiation, temperature and relative humidity) is presented. Then the error propagation analysis is made for net radiation and for reference evapotranspiration. Data from the Raimat weather station, which is located in the Catalonia region of Spain, are used to illustrate the error relationships. The results show that temperature, relative humidity and cloud cover errors have little effect on the net radiation or reference evapotranspiration. A 5°C error in estimating surface temperature leads to errors as big as 30 W m −2 at high temperature. A 4% solar radiation (R s ) error can cause a net radiation error as big as 26 W m −2 when R s ≈ 1000 W m −2 . However, the error is less when cloud cover is calculated as a function of the solar radiation. The absolute error in reference evapotranspiration (ET o ) equals the product of the net radiation error and the radiation term weighting factor [W = Δ(Δ1+γ)] in the ET o equation. Therefore, the ET o error varies between 65 and 85% of the R n error as air temperature increases from about 20° to 40°C. (author)

(How) do we learn from errors? A prospective study of the link between the ward's learning practices and medication administration errors.

Science.gov (United States)

Drach-Zahavy, A; Somech, A; Admi, H; Peterfreund, I; Peker, H; Priente, O

2014-03-01

Attention in the ward should shift from preventing medication administration errors to managing them. Nevertheless, little is known in regard with the practices nursing wards apply to learn from medication administration errors as a means of limiting them. To test the effectiveness of four types of learning practices, namely, non-integrated, integrated, supervisory and patchy learning practices in limiting medication administration errors. Data were collected from a convenient sample of 4 hospitals in Israel by multiple methods (observations and self-report questionnaires) at two time points. The sample included 76 wards (360 nurses). Medication administration error was defined as any deviation from prescribed medication processes and measured by a validated structured observation sheet. Wards' use of medication administration technologies, location of the medication station, and workload were observed; learning practices and demographics were measured by validated questionnaires. Results of the mixed linear model analysis indicated that the use of technology and quiet location of the medication cabinet were significantly associated with reduced medication administration errors (estimate=.03, perrors (estimate=.04, plearning practices, supervisory learning was the only practice significantly linked to reduced medication administration errors (estimate=-.04, plearning were significantly linked to higher levels of medication administration errors (estimate=-.03, plearning was not associated with it (p>.05). How wards manage errors might have implications for medication administration errors beyond the effects of typical individual, organizational and technology risk factors. Head nurse can facilitate learning from errors by "management by walking around" and monitoring nurses' medication administration behaviors. Copyright © 2013 Elsevier Ltd. All rights reserved.

Galaxy Cluster Shapes and Systematic Errors in H_0 as Determined by the Sunyaev-Zel'dovich Effect

Science.gov (United States)

Sulkanen, Martin E.; Patel, Sandeep K.

1998-01-01

Imaging of the Sunyaev-Zeldovich (SZ) effect in galaxy clusters combined with cluster plasma x-ray diagnostics promises to measure the cosmic distance scale to high accuracy. However, projecting the inverse-Compton scattering and x-ray emission along the cluster line-of-sight will introduce systematic error's in the Hubble constant, H_0, because the true shape of the cluster is not known. In this paper we present a study of the systematic errors in the value of H_0, as determined by the x-ray and SZ properties of theoretical samples of triaxial isothermal "beta-model" clusters, caused by projection effects and observer orientation relative to the model clusters' principal axes. We calculate three estimates for H_0 for each cluster, based on their large and small apparent angular core radii, and their arithmetic mean. We average the estimates for H_0 for a sample of 25 clusters and find that the estimates have limited systematic error: the 99.7% confidence intervals for the mean estimated H_0 analyzing the clusters using either their large or mean angular core r;dius are within 14% of the "true" (assumed) value of H_0 (and enclose it), for a triaxial beta model cluster sample possessing a distribution of apparent x-ray cluster ellipticities consistent with that of observed x-ray clusters.

Safe and effective error rate monitors for SS7 signaling links

Science.gov (United States)

Schmidt, Douglas C.

1994-04-01

This paper describes SS7 error monitor characteristics, discusses the existing SUERM (Signal Unit Error Rate Monitor), and develops the recently proposed EIM (Error Interval Monitor) for higher speed SS7 links. A SS7 error monitor is considered safe if it ensures acceptable link quality and is considered effective if it is tolerant to short-term phenomena. Formal criteria for safe and effective error monitors are formulated in this paper. This paper develops models of changeover transients, the unstable component of queue length resulting from errors. These models are in the form of recursive digital filters. Time is divided into sequential intervals. The filter's input is the number of errors which have occurred in each interval. The output is the corresponding change in transmit queue length. Engineered EIM's are constructed by comparing an estimated changeover transient with a threshold T using a transient model modified to enforce SS7 standards. When this estimate exceeds T, a changeover will be initiated and the link will be removed from service. EIM's can be differentiated from SUERM by the fact that EIM's monitor errors over an interval while SUERM's count errored messages. EIM's offer several advantages over SUERM's, including the fact that they are safe and effective, impose uniform standards in link quality, are easily implemented, and make minimal use of real-time resources.

Impact of shrinking measurement error budgets on qualification metrology sampling and cost

Science.gov (United States)

Sendelbach, Matthew; Sarig, Niv; Wakamoto, Koichi; Kim, Hyang Kyun (Helen); Isbester, Paul; Asano, Masafumi; Matsuki, Kazuto; Vaid, Alok; Osorio, Carmen; Archie, Chas

2014-04-01

When designing an experiment to assess the accuracy of a tool as compared to a reference tool, semiconductor metrologists are often confronted with the situation that they must decide on the sampling strategy before the measurements begin. This decision is usually based largely on the previous experience of the metrologist and the available resources, and not on the statistics that are needed to achieve acceptable confidence limits on the final result. This paper shows a solution to this problem, called inverse TMU analysis, by presenting statistically-based equations that allow the user to estimate the needed sampling after providing appropriate inputs, allowing him to make important "risk vs. reward" sampling, cost, and equipment decisions. Application examples using experimental data from scatterometry and critical dimension scanning electron microscope (CD-SEM) tools are used first to demonstrate how the inverse TMU analysis methodology can be used to make intelligent sampling decisions before the start of the experiment, and then to reveal why low sampling can lead to unstable and misleading results. A model is developed that can help an experimenter minimize the costs associated both with increased sampling and with making wrong decisions caused by insufficient sampling. A second cost model is described that reveals the inadequacy of current TEM (Transmission Electron Microscopy) sampling practices and the enormous costs associated with TEM sampling that is needed to provide reasonable levels of certainty in the result. These high costs reach into the tens of millions of dollars for TEM reference metrology as the measurement error budgets reach angstrom levels. The paper concludes with strategies on how to manage and mitigate these costs.

Effect of measurement error budgets and hybrid metrology on qualification metrology sampling

Science.gov (United States)

Sendelbach, Matthew; Sarig, Niv; Wakamoto, Koichi; Kim, Hyang Kyun (Helen); Isbester, Paul; Asano, Masafumi; Matsuki, Kazuto; Osorio, Carmen; Archie, Chas

2014-10-01

Until now, metrologists had no statistics-based method to determine the sampling needed for an experiment before the start that accuracy experiment. We show a solution to this problem called inverse total measurement uncertainty (TMU) analysis, by presenting statistically based equations that allow the user to estimate the needed sampling after providing appropriate inputs, allowing him to make important "risk versus reward" sampling, cost, and equipment decisions. Application examples using experimental data from scatterometry and critical dimension scanning electron microscope tools are used first to demonstrate how the inverse TMU analysis methodology can be used to make intelligent sampling decisions and then to reveal why low sampling can lead to unstable and misleading results. One model is developed that can help experimenters minimize sampling costs. A second cost model reveals the inadequacy of some current sampling practices-and the enormous costs associated with sampling that provides reasonable levels of certainty in the result. We introduce the strategies on how to manage and mitigate these costs and begin the discussion on how fabs are able to manufacture devices using minimal reference sampling when qualifying metrology steps. Finally, the relationship between inverse TMU analysis and hybrid metrology is explored.

The effect of experimental sleep fragmentation on error monitoring.

Science.gov (United States)

Ko, Cheng-Hung; Fang, Ya-Wen; Tsai, Ling-Ling; Hsieh, Shulan

2015-01-01

Experimental sleep fragmentation (SF) is characterized by frequent brief arousals without reduced total sleep time and causes daytime sleepiness and impaired neurocognitive processes. This study explored the impact of SF on error monitoring. Thirteen adults underwent auditory stimuli-induced high-level (H) and low-level (L) SF nights. Flanker task performance and electroencephalogram data were collected in the morning following SF nights. Compared to LSF, HSF induced more arousals and stage N1 sleep, decreased slow wave sleep and rapid-eye-movement sleep (REMS), decreased subjective sleep quality, increased daytime sleepiness, and decreased amplitudes of P300 and error-related positivity (Pe). SF effects on N1 sleep were negatively correlated with SF effects on the Pe amplitude. Furthermore, as REMS was reduced by SF, post-error accuracy compensations were greatly reduced. In conclusion, attentional processes and error monitoring were impaired following one night of frequent sleep disruptions, even when total sleep time was not reduced. Copyright © 2014 Elsevier B.V. All rights reserved.

Effects of Shame and Guilt on Error Reporting Among Obstetric Clinicians.

Science.gov (United States)

Zabari, Mara Lynne; Southern, Nancy L

2018-04-17

To understand how the experiences of shame and guilt, coupled with organizational factors, affect error reporting by obstetric clinicians. Descriptive cross-sectional. A sample of 84 obstetric clinicians from three maternity units in Washington State. In this quantitative inquiry, a variant of the Test of Self-Conscious Affect was used to measure proneness to guilt and shame. In addition, we developed questions to assess attitudes regarding concerns about damaging one's reputation if an error was reported and the choice to keep an error to oneself. Both assessments were analyzed separately and then correlated to identify relationships between constructs. Interviews were used to identify organizational factors that affect error reporting. As a group, mean scores indicated that obstetric clinicians would not choose to keep errors to themselves. However, bivariate correlations showed that proneness to shame was positively correlated to concerns about one's reputation if an error was reported, and proneness to guilt was negatively correlated with keeping errors to oneself. Interview data analysis showed that Past Experience with Responses to Errors, Management and Leadership Styles, Professional Hierarchy, and Relationships With Colleagues were influential factors in error reporting. Although obstetric clinicians want to report errors, their decisions to report are influenced by their proneness to guilt and shame and perceptions of the degree to which organizational factors facilitate or create barriers to restore their self-images. Findings underscore the influence of the organizational context on clinicians' decisions to report errors. Copyright © 2018 AWHONN, the Association of Women’s Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

Effect of refractive error on temperament and character properties

Institute of Scientific and Technical Information of China (English)

Emine; Kalkan; Akcay; Fatih; Canan; Huseyin; Simavli; Derya; Dal; Hacer; Yalniz; Nagihan; Ugurlu; Omer; Gecici; Nurullah; Cagil

2015-01-01

AIM: To determine the effect of refractive error on temperament and character properties using Cloninger’s psychobiological model of personality.METHODS: Using the Temperament and Character Inventory(TCI), the temperament and character profiles of 41 participants with refractive errors(17 with myopia,12 with hyperopia, and 12 with myopic astigmatism) were compared to those of 30 healthy control participants.Here, temperament comprised the traits of novelty seeking, harm-avoidance, and reward dependence, while character comprised traits of self-directedness,cooperativeness, and self-transcendence.RESULTS: Participants with refractive error showed significantly lower scores on purposefulness,cooperativeness, empathy, helpfulness, and compassion(P <0.05, P <0.01, P <0.05, P <0.05, and P <0.01,respectively).CONCLUSION: Refractive error might have a negative influence on some character traits, and different types of refractive error might have different temperament and character properties. These personality traits may be implicated in the onset and/or perpetuation of refractive errors and may be a productive focus for psychotherapy.

Errors in dual x-ray beam differential absorptiometry

International Nuclear Information System (INIS)

Bolin, F.; Preuss, L.; Gilbert, K.; Bugenis, C.

1977-01-01

Errors pertinent to the dual beam absorptiometry system have been studied and five areas are given in detail: (1) scattering, in which a computer analysis of multiple scattering shows little error due to this effect; (2) geometrical configuration effects, in which the slope of the sample is shown to influence the accuracy of the measurement; (3) Poisson variations, wherein it is shown that a simultaneous reduction can be obtained in both dosage and statistical error; (4) absorption coefficients, in which the effect of variation in absorption coefficient compilations is shown to have a critical effect on the interpretations of experimental data; and (5) filtering, wherein is shown the need for filters on dual beam systems using a characteristic x-ray output. A zero filter system is outlined

Effect of Pharmacist Participation During Physician Rounds and Prescription Error in the Intensive Care Unit

Directory of Open Access Journals (Sweden)

Marlina A. Turnodihardjo

2016-09-01

Full Text Available Patient’s safety is now a prominent issue in pharmaceutical care because of adverse drug events that is common in hospitalized patients. Majority of error are likely occured during prescribing, which is the first stage of pharmacy process. Prescription errors mostly occured in an Intensive Care Unit (ICU, which is due to the severity of the illness of its patients as well as the large number of medications prescribed. Pharmacist participation actually could reduce prescribing error made by doctors. The main objective of this study was to determine the effect of pharmacist participation during physician rounds on prescription errors in the ICU. This study was a quasi-experimental design with one group pre-post test. A prospective study was conducted from April to May 2015 by screening 110 samples of orders. Screening was done to identify type of prescription errors. Prescription error was defined as error in the prescription writing process – incomplete information and not according to agreement. Mann-Whitney test was used to analyze the differences in prescribing errors. The results showed that there was the differences between prescription errors before and during the pharmacist participation (p<0.05. There was also a significant negative correlation between the frequency of pharmacist recommendation on drug ordering and prescription errors (r= –0.638; p<0.05. It means the pharmacist participation was one of the strategies that can be adopted to prevent in prescribing errors and implementation of collaboration between both doctors and pharmacists. In other words, the supporting hospital management system which would encourage interpersonal communication among health care proffesionals is needed.

Death Certification Errors and the Effect on Mortality Statistics.

Science.gov (United States)

McGivern, Lauri; Shulman, Leanne; Carney, Jan K; Shapiro, Steven; Bundock, Elizabeth

Errors in cause and manner of death on death certificates are common and affect families, mortality statistics, and public health research. The primary objective of this study was to characterize errors in the cause and manner of death on death certificates completed by non-Medical Examiners. A secondary objective was to determine the effects of errors on national mortality statistics. We retrospectively compared 601 death certificates completed between July 1, 2015, and January 31, 2016, from the Vermont Electronic Death Registration System with clinical summaries from medical records. Medical Examiners, blinded to original certificates, reviewed summaries, generated mock certificates, and compared mock certificates with original certificates. They then graded errors using a scale from 1 to 4 (higher numbers indicated increased impact on interpretation of the cause) to determine the prevalence of minor and major errors. They also compared International Classification of Diseases, 10th Revision (ICD-10) codes on original certificates with those on mock certificates. Of 601 original death certificates, 319 (53%) had errors; 305 (51%) had major errors; and 59 (10%) had minor errors. We found no significant differences by certifier type (physician vs nonphysician). We did find significant differences in major errors in place of death ( P statistics. Surveillance and certifier education must expand beyond local and state efforts. Simplifying and standardizing underlying literal text for cause of death may improve accuracy, decrease coding errors, and improve national mortality statistics.

Bandwagon effects and error bars in particle physics

Science.gov (United States)

Jeng, Monwhea

2007-02-01

We study historical records of experiments on particle masses, lifetimes, and widths, both for signs of expectation bias, and to compare actual errors with reported error bars. We show that significant numbers of particle properties exhibit "bandwagon effects": reported values show trends and clustering as a function of the year of publication, rather than random scatter about the mean. While the total amount of clustering is significant, it is also fairly small; most individual particle properties do not display obvious clustering. When differences between experiments are compared with the reported error bars, the deviations do not follow a normal distribution, but instead follow an exponential distribution for up to ten standard deviations.

Bandwagon effects and error bars in particle physics

International Nuclear Information System (INIS)

Jeng, Monwhea

2007-01-01

We study historical records of experiments on particle masses, lifetimes, and widths, both for signs of expectation bias, and to compare actual errors with reported error bars. We show that significant numbers of particle properties exhibit 'bandwagon effects': reported values show trends and clustering as a function of the year of publication, rather than random scatter about the mean. While the total amount of clustering is significant, it is also fairly small; most individual particle properties do not display obvious clustering. When differences between experiments are compared with the reported error bars, the deviations do not follow a normal distribution, but instead follow an exponential distribution for up to ten standard deviations

A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

Directory of Open Access Journals (Sweden)

Githure John I

2009-09-01

Full Text Available Abstract Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression. The eigenfunction

Understanding reliance on automation: effects of error type, error distribution, age and experience

Science.gov (United States)

Sanchez, Julian; Rogers, Wendy A.; Fisk, Arthur D.; Rovira, Ericka

2015-01-01

An obstacle detection task supported by “imperfect” automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation. PMID:25642142

The effectiveness of risk management program on pediatric nurses' medication error.

Science.gov (United States)

Dehghan-Nayeri, Nahid; Bayat, Fariba; Salehi, Tahmineh; Faghihzadeh, Soghrat

2013-09-01

Medication therapy is one of the most complex and high-risk clinical processes that nurses deal with. Medication error is the most common type of error that brings about damage and death to patients, especially pediatric ones. However, these errors are preventable. Identifying and preventing undesirable events leading to medication errors are the main risk management activities. The aim of this study was to investigate the effectiveness of a risk management program on the pediatric nurses' medication error rate. This study is a quasi-experimental one with a comparison group. In this study, 200 nurses were recruited from two main pediatric hospitals in Tehran. In the experimental hospital, we applied the risk management program for a period of 6 months. Nurses of the control hospital did the hospital routine schedule. A pre- and post-test was performed to measure the frequency of the medication error events. SPSS software, t-test, and regression analysis were used for data analysis. After the intervention, the medication error rate of nurses at the experimental hospital was significantly lower (P error-reporting rate was higher (P medical environment, applying the quality-control programs such as risk management can effectively prevent the occurrence of the hospital undesirable events. Nursing mangers can reduce the medication error rate by applying risk management programs. However, this program cannot succeed without nurses' cooperation.

A novel knot selection method for the error-bounded B-spline curve fitting of sampling points in the measuring process

International Nuclear Information System (INIS)

Liang, Fusheng; Zhao, Ji; Ji, Shijun; Zhang, Bing; Fan, Cheng

2017-01-01

The B-spline curve has been widely used in the reconstruction of measurement data. The error-bounded sampling points reconstruction can be achieved by the knot addition method (KAM) based B-spline curve fitting. In KAM, the selection pattern of initial knot vector has been associated with the ultimate necessary number of knots. This paper provides a novel initial knots selection method to condense the knot vector required for the error-bounded B-spline curve fitting. The initial knots are determined by the distribution of features which include the chord length (arc length) and bending degree (curvature) contained in the discrete sampling points. Firstly, the sampling points are fitted into an approximate B-spline curve Gs with intensively uniform knot vector to substitute the description of the feature of the sampling points. The feature integral of Gs is built as a monotone increasing function in an analytic form. Then, the initial knots are selected according to the constant increment of the feature integral. After that, an iterative knot insertion (IKI) process starting from the initial knots is introduced to improve the fitting precision, and the ultimate knot vector for the error-bounded B-spline curve fitting is achieved. Lastly, two simulations and the measurement experiment are provided, and the results indicate that the proposed knot selection method can reduce the number of ultimate knots available. (paper)

Effects of variable transformations on errors in FORM results

International Nuclear Information System (INIS)

Qin Quan; Lin Daojin; Mei Gang; Chen Hao

2006-01-01

On the basis of studies on second partial derivatives of the variable transformation functions for nine different non-normal variables the paper comprehensively discusses the effects of the transformation on FORM results and shows that senses and values of the errors in FORM results depend on distributions of the basic variables, whether resistances or actions basic variables represent, and the design point locations in the standard normal space. The transformations of the exponential or Gamma resistance variables can generate +24% errors in the FORM failure probability, and the transformation of Frechet action variables could generate -31% errors

Leniency programs and socially beneficial cooperation: Effects of type I errors

Directory of Open Access Journals (Sweden)

Natalia Pavlova

2016-12-01

Full Text Available This study operationalizes the concept of hostility tradition in antitrust as mentioned by Oliver Williamson and Ronald Coase through erroneous law enforcement effects. The antitrust agency may commit type I, not just type II, errors when evaluating an agreement in terms of cartels. Moreover, firms can compete in a standard way, collude or engage in cooperative agreements that improve efficiency. The antitrust agency may misinterpret such cooperative agreements, committing a type I error (over-enforcement. The model set-up is drawn from Motta and Polo (2003 and is extended as described above using the findings of Ghebrihiwet and Motchenkova (2010. Three effects play a role in this environment. Type I errors may induce firms that would engage in socially efficient cooperation absent errors to opt for collusion (the deserved punishment effect. For other parameter configurations, type I errors may interrupt ongoing cooperation when investigated. In this case, the firms falsely report collusion and apply for leniency, fearing being erroneously fined (the disrupted cooperation effect. Finally, over-enforcement may prevent beneficial cooperation from starting given the threat of being mistakenly fined (the prevented cooperation effect. The results help us understand the negative impact that a hostility tradition in antitrust — which is more likely for inexperienced regimes and regimes with low standards of evidence — and the resulting type I enforcement errors can have on social welfare when applied to the regulation of horizontal agreements. Additional interpretations are discussed in light of leniency programs for corruption and compliance policies for antitrust violations.

Total error components - isolation of laboratory variation from method performance

International Nuclear Information System (INIS)

Bottrell, D.; Bleyler, R.; Fisk, J.; Hiatt, M.

1992-01-01

The consideration of total error across sampling and analytical components of environmental measurements is relatively recent. The U.S. Environmental Protection Agency (EPA), through the Contract Laboratory Program (CLP), provides complete analyses and documented reports on approximately 70,000 samples per year. The quality assurance (QA) functions of the CLP procedures provide an ideal data base-CLP Automated Results Data Base (CARD)-to evaluate program performance relative to quality control (QC) criteria and to evaluate the analysis of blind samples. Repetitive analyses of blind samples within each participating laboratory provide a mechanism to separate laboratory and method performance. Isolation of error sources is necessary to identify effective options to establish performance expectations, and to improve procedures. In addition, optimized method performance is necessary to identify significant effects that result from the selection among alternative procedures in the data collection process (e.g., sampling device, storage container, mode of sample transit, etc.). This information is necessary to evaluate data quality; to understand overall quality; and to provide appropriate, cost-effective information required to support a specific decision

Effects of averaging over motion and the resulting systematic errors in radiation therapy

International Nuclear Information System (INIS)

Evans, Philip M; Coolens, Catherine; Nioutsikou, Elena

2006-01-01

The potential for systematic errors in radiotherapy of a breathing patient is considered using the statistical model of Bortfeld et al (2002 Phys. Med. Biol. 47 2203-20). It is shown that although averaging over 30 fractions does result in a narrow Gaussian distribution of errors, as predicted by the central limit theorem, the fact that one or a few samples of the breathing patient's motion distribution are used for treatment planning (in contrast to the many treatment fractions that are likely to be delivered) may result in a much larger error with a systematic component. The error distribution may be particularly large if a scan at breath-hold is used for planning. (note)

Influence of random setup error on dose distribution

International Nuclear Information System (INIS)

Zhai Zhenyu

2008-01-01

Objective: To investigate the influence of random setup error on dose distribution in radiotherapy and determine the margin from ITV to PTV. Methods: A random sample approach was used to simulate the fields position in target coordinate system. Cumulative effect of random setup error was the sum of dose distributions of all individual treatment fractions. Study of 100 cumulative effects might get shift sizes of 90% dose point position. Margins from ITV to PTV caused by random setup error were chosen by 95% probability. Spearman's correlation was used to analyze the influence of each factor. Results: The average shift sizes of 90% dose point position was 0.62, 1.84, 3.13, 4.78, 6.34 and 8.03 mm if random setup error was 1,2,3,4,5 and 6 mm,respectively. Univariate analysis showed the size of margin was associated only by the size of random setup error. Conclusions: Margin of ITV to PTV is 1.2 times random setup error for head-and-neck cancer and 1.5 times for thoracic and abdominal cancer. Field size, energy and target depth, unlike random setup error, have no relation with the size of the margin. (authors)

Effect of error propagation of nuclide number densities on Monte Carlo burn-up calculations

International Nuclear Information System (INIS)

Tohjoh, Masayuki; Endo, Tomohiro; Watanabe, Masato; Yamamoto, Akio

2006-01-01

As a result of improvements in computer technology, the continuous energy Monte Carlo burn-up calculation has received attention as a good candidate for an assembly calculation method. However, the results of Monte Carlo calculations contain the statistical errors. The results of Monte Carlo burn-up calculations, in particular, include propagated statistical errors through the variance of the nuclide number densities. Therefore, if statistical error alone is evaluated, the errors in Monte Carlo burn-up calculations may be underestimated. To make clear this effect of error propagation on Monte Carlo burn-up calculations, we here proposed an equation that can predict the variance of nuclide number densities after burn-up calculations, and we verified this equation using enormous numbers of the Monte Carlo burn-up calculations by changing only the initial random numbers. We also verified the effect of the number of burn-up calculation points on Monte Carlo burn-up calculations. From these verifications, we estimated the errors in Monte Carlo burn-up calculations including both statistical and propagated errors. Finally, we made clear the effects of error propagation on Monte Carlo burn-up calculations by comparing statistical errors alone versus both statistical and propagated errors. The results revealed that the effects of error propagation on the Monte Carlo burn-up calculations of 8 x 8 BWR fuel assembly are low up to 60 GWd/t

Modulated error diffusion CGHs for neural nets

Science.gov (United States)

Vermeulen, Pieter J. E.; Casasent, David P.

1990-05-01

New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

[Patient identification errors and biological samples in the analytical process: Is it possible to improve patient safety?].

Science.gov (United States)

Cuadrado-Cenzual, M A; García Briñón, M; de Gracia Hills, Y; González Estecha, M; Collado Yurrita, L; de Pedro Moro, J A; Fernández Pérez, C; Arroyo Fernández, M

2015-01-01

Patient identification errors and biological samples are one of the problems with the highest risk factor in causing an adverse event in the patient. To detect and analyse the causes of patient identification errors in analytical requests (PIEAR) from emergency departments, and to develop improvement strategies. A process and protocol was designed, to be followed by all professionals involved in the requesting and performing of laboratory tests. Evaluation and monitoring indicators of PIEAR were determined, before and after the implementation of these improvement measures (years 2010-2014). A total of 316 PIEAR were detected in a total of 483,254 emergency service requests during the study period, representing a mean of 6.80/10,000 requests. Patient identification failure was the most frequent in all the 6-monthly periods assessed, with a significant difference (Perrors. However, we must continue working with this strategy, promoting a culture of safety for all the professionals involved, and trying to achieve the goal that 100% of the analytical and samples are properly identified. Copyright © 2015 SECA. Published by Elsevier Espana. All rights reserved.

Analysis of methods commonly used in biomedicine for treatment versus control comparison of very small samples.

Science.gov (United States)

Ristić-Djurović, Jasna L; Ćirković, Saša; Mladenović, Pavle; Romčević, Nebojša; Trbovich, Alexander M

2018-04-01

A rough estimate indicated that use of samples of size not larger than ten is not uncommon in biomedical research and that many of such studies are limited to strong effects due to sample sizes smaller than six. For data collected from biomedical experiments it is also often unknown if mathematical requirements incorporated in the sample comparison methods are satisfied. Computer simulated experiments were used to examine performance of methods for qualitative sample comparison and its dependence on the effectiveness of exposure, effect intensity, distribution of studied parameter values in the population, and sample size. The Type I and Type II errors, their average, as well as the maximal errors were considered. The sample size 9 and the t-test method with p = 5% ensured error smaller than 5% even for weak effects. For sample sizes 6-8 the same method enabled detection of weak effects with errors smaller than 20%. If the sample sizes were 3-5, weak effects could not be detected with an acceptable error; however, the smallest maximal error in the most general case that includes weak effects is granted by the standard error of the mean method. The increase of sample size from 5 to 9 led to seven times more accurate detection of weak effects. Strong effects were detected regardless of the sample size and method used. The minimal recommended sample size for biomedical experiments is 9. Use of smaller sizes and the method of their comparison should be justified by the objective of the experiment. Copyright © 2018 Elsevier B.V. All rights reserved.

The Effect of Divided Attention on Inhibiting the Gravity Error

Science.gov (United States)

Hood, Bruce M.; Wilson, Alice; Dyson, Sally

2006-01-01

Children who could overcome the gravity error on Hood's (1995) tubes task were tested in a condition where they had to monitor two falling balls. This condition significantly impaired search performance with the majority of mistakes being gravity errors. In a second experiment, the effect of monitoring two balls was compared in the tubes task and…

Validation of Metrics as Error Predictors

Science.gov (United States)

Mendling, Jan

In this chapter, we test the validity of metrics that were defined in the previous chapter for predicting errors in EPC business process models. In Section 5.1, we provide an overview of how the analysis data is generated. Section 5.2 describes the sample of EPCs from practice that we use for the analysis. Here we discuss a disaggregation by the EPC model group and by error as well as a correlation analysis between metrics and error. Based on this sample, we calculate a logistic regression model for predicting error probability with the metrics as input variables in Section 5.3. In Section 5.4, we then test the regression function for an independent sample of EPC models from textbooks as a cross-validation. Section 5.5 summarizes the findings.

Effects of learning climate and registered nurse staffing on medication errors.

Science.gov (United States)

Chang, YunKyung; Mark, Barbara

2011-01-01

Despite increasing recognition of the significance of learning from errors, little is known about how learning climate contributes to error reduction. The purpose of this study was to investigate whether learning climate moderates the relationship between error-producing conditions and medication errors. A cross-sectional descriptive study was done using data from 279 nursing units in 146 randomly selected hospitals in the United States. Error-producing conditions included work environment factors (work dynamics and nurse mix), team factors (communication with physicians and nurses' expertise), personal factors (nurses' education and experience), patient factors (age, health status, and previous hospitalization), and medication-related support services. Poisson models with random effects were used with the nursing unit as the unit of analysis. A significant negative relationship was found between learning climate and medication errors. It also moderated the relationship between nurse mix and medication errors: When learning climate was negative, having more registered nurses was associated with fewer medication errors. However, no relationship was found between nurse mix and medication errors at either positive or average levels of learning climate. Learning climate did not moderate the relationship between work dynamics and medication errors. The way nurse mix affects medication errors depends on the level of learning climate. Nursing units with fewer registered nurses and frequent medication errors should examine their learning climate. Future research should be focused on the role of learning climate as related to the relationships between nurse mix and medication errors.

Sample size and classification error for Bayesian change-point models with unlabelled sub-groups and incomplete follow-up.

Science.gov (United States)

White, Simon R; Muniz-Terrera, Graciela; Matthews, Fiona E

2018-05-01

Many medical (and ecological) processes involve the change of shape, whereby one trajectory changes into another trajectory at a specific time point. There has been little investigation into the study design needed to investigate these models. We consider the class of fixed effect change-point models with an underlying shape comprised two joined linear segments, also known as broken-stick models. We extend this model to include two sub-groups with different trajectories at the change-point, a change and no change class, and also include a missingness model to account for individuals with incomplete follow-up. Through a simulation study, we consider the relationship of sample size to the estimates of the underlying shape, the existence of a change-point, and the classification-error of sub-group labels. We use a Bayesian framework to account for the missing labels, and the analysis of each simulation is performed using standard Markov chain Monte Carlo techniques. Our simulation study is inspired by cognitive decline as measured by the Mini-Mental State Examination, where our extended model is appropriate due to the commonly observed mixture of individuals within studies who do or do not exhibit accelerated decline. We find that even for studies of modest size ( n = 500, with 50 individuals observed past the change-point) in the fixed effect setting, a change-point can be detected and reliably estimated across a range of observation-errors.

Investigation of experimental pole-figure errors by simulation of individual spectra

International Nuclear Information System (INIS)

Lychagina, T. A.; Nikolaev, D. I.

2007-01-01

The errors in measuring the crystallographic texture described by pole figures are studied. A set of diffraction spectra for a sample of the MA2-1 alloy (Mg + 4.5% Al + 1% Zn) are measured, simulation of individual spectra on the basis of which the pole figures were obtained is performed, and their errors are determined. The conclusion about the possibility of determining the effect of errors of the diffraction peak half-width on the pole figure errors that was drawn in our previous studies is confirmed

The Effects of Discrete-Trial Training Commission Errors on Learner Outcomes: An Extension

Science.gov (United States)

Jenkins, Sarah R.; Hirst, Jason M.; DiGennaro Reed, Florence D.

2015-01-01

We conducted a parametric analysis of treatment integrity errors during discrete-trial training and investigated the effects of three integrity conditions (0, 50, or 100 % errors of commission) on performance in the presence and absence of programmed errors. The presence of commission errors impaired acquisition for three of four participants.…

New PAT tools for assessing content uniformity, sampling error, and degree of crystallinity in pharmaceutical tablets

DEFF Research Database (Denmark)

Warnecke, Solveig

of the pharmaceutical drug, both during development and throughout the production. The usage of PAT tools is encouraged by the regulatory authorities, and therefore the interest in new and improved PAT tools is increasing. The main purpose of introducing Quality by Design (QbD) and PAT in pharmaceutical production...... practice in traditional pharmaceutical industry. In this thesis, three spectroscopic PAT tools are investigated, near-infrared-, terahertz-, and fluorescence-spectroscopy. These techniques have been evaluated with chemometrics and theory of sampling. The first study focused on the critical but rather...... overlooked sampling uncertainty that exist in all analytical measurements. The sampling error was studied using an example involving near infrared transmission (NIT) spectroscopy to study content of uniformity of five batches of escitalopram tablets, produced at different active pharmaceutical ingredients...

[Errors in Peruvian medical journals references].

Science.gov (United States)

Huamaní, Charles; Pacheco-Romero, José

2009-01-01

References are fundamental in our studies; an adequate selection is asimportant as an adequate description. To determine the number of errors in a sample of references found in Peruvian medical journals. We reviewed 515 scientific papers references selected by systematic randomized sampling and corroborated reference information with the original document or its citation in Pubmed, LILACS or SciELO-Peru. We found errors in 47,6% (245) of the references, identifying 372 types of errors; the most frequent were errors in presentation style (120), authorship (100) and title (100), mainly due to spelling mistakes (91). References error percentage was high, varied and multiple. We suggest systematic revision of references in the editorial process as well as to extend the discussion on this theme. references, periodicals, research, bibliometrics.

Error correcting circuit design with carbon nanotube field effect transistors

Science.gov (United States)

Liu, Xiaoqiang; Cai, Li; Yang, Xiaokuo; Liu, Baojun; Liu, Zhongyong

2018-03-01

In this work, a parallel error correcting circuit based on (7, 4) Hamming code is designed and implemented with carbon nanotube field effect transistors, and its function is validated by simulation in HSpice with the Stanford model. A grouping method which is able to correct multiple bit errors in 16-bit and 32-bit application is proposed, and its error correction capability is analyzed. Performance of circuits implemented with CNTFETs and traditional MOSFETs respectively is also compared, and the former shows a 34.4% decrement of layout area and a 56.9% decrement of power consumption.

Calculation error of collective effective dose of external exposure during works at 'Shelter' object

International Nuclear Information System (INIS)

Batij, V.G.; Derengovskij, V.V.; Kochnev, N.A.; Sizov, A.A.

2001-01-01

Collective effective dose (CED) error assessment is the most important task for optimal planning of works in the 'Shelter' object conditions. The main components of CED error are as follows: error in transient factor determination from exposition dose to equivalent dose; error in working hours determination in 'Shelter' object conditions; error in determination of dose rate at workplaces; additional CED error introduced by shielding of workplaces

The effects of forecast errors on the merchandising of wind power

International Nuclear Information System (INIS)

Roon, Serafin von

2012-01-01

A permanent balance between consumption and generation is essential for a stable supply of electricity. In order to ensure this balance, all relevant load data have to be announced for the following day. Consequently, a day-ahead forecast of the wind power generation is required, which also forms the basis for the sale of the wind power at the wholesale market. The main subject of the study is the short-term power supply, which compensates errors in wind power forecasting for balancing the wind power forecast errors at short notice. These forecast errors effects the revenues and the expenses by selling and buying power in the day-ahead, intraday and balance energy market. These price effects resulting from the forecast errors are derived from an empirical analysis. In a scenario for the year 2020 the potential of conventional power plants to supply power at short notice is evaluated from a technical and economic point of view by a time series analysis and a unit commitment simulation.

ٍEffective factors on the Incidence of medication errors from the nursing staff perspective in various department of Fasa Hospital

Directory of Open Access Journals (Sweden)

Mostafa Bizhani

2013-06-01

Full Text Available  Background and Objective: The incidence of medical errors is deemed one of the unavoidable cases of serious threats to the health and safety of patients. This study aimed to determine the factors influencing medication errors from the perspective of the nursing staff. Materials and Methods: This descriptive -analytic study recruited 80 nurses working in various wards in Fasa Hospital. The nurses were selected via the availability sampling method, and their perspective on factors affecting medication errors was gathered using a questionnaire designed for this study. The data were analyzed with SPSS-15 software.   Results: The most important causes of medication errors were work fatigue, low nurse-to-patient ratio, long working hours, high density of work in units, and doing other tasks. Other variables such as age and gender as well as factors effective on the incidence of medication errors are mentioned in the full text. Conclusion: From the nurses’ standpoint, workload and the patient-to-nurse ratio were the most significant factors leading to medication errors.

Violation of the Sphericity Assumption and Its Effect on Type-I Error Rates in Repeated Measures ANOVA and Multi-Level Linear Models (MLM).

Science.gov (United States)

Haverkamp, Nicolas; Beauducel, André

2017-01-01

We investigated the effects of violations of the sphericity assumption on Type I error rates for different methodical approaches of repeated measures analysis using a simulation approach. In contrast to previous simulation studies on this topic, up to nine measurement occasions were considered. Effects of the level of inter-correlations between measurement occasions on Type I error rates were considered for the first time. Two populations with non-violation of the sphericity assumption, one with uncorrelated measurement occasions and one with moderately correlated measurement occasions, were generated. One population with violation of the sphericity assumption combines uncorrelated with highly correlated measurement occasions. A second population with violation of the sphericity assumption combines moderately correlated and highly correlated measurement occasions. From these four populations without any between-group effect or within-subject effect 5,000 random samples were drawn. Finally, the mean Type I error rates for Multilevel linear models (MLM) with an unstructured covariance matrix (MLM-UN), MLM with compound-symmetry (MLM-CS) and for repeated measures analysis of variance (rANOVA) models (without correction, with Greenhouse-Geisser-correction, and Huynh-Feldt-correction) were computed. To examine the effect of both the sample size and the number of measurement occasions, sample sizes of n = 20, 40, 60, 80, and 100 were considered as well as measurement occasions of m = 3, 6, and 9. With respect to rANOVA, the results plead for a use of rANOVA with Huynh-Feldt-correction, especially when the sphericity assumption is violated, the sample size is rather small and the number of measurement occasions is large. For MLM-UN, the results illustrate a massive progressive bias for small sample sizes ( n = 20) and m = 6 or more measurement occasions. This effect could not be found in previous simulation studies with a smaller number of measurement occasions. The

[Nature or nurture: effects of parental ametropia on children's refractive errors].

Science.gov (United States)

Landmann, A; Bechrakis, E

2013-12-01

The aim of this study was to quantify the degree of association between juvenile refraction errors and parental refraction status. Using a simple questionnaire we conducted a cross-sectional study to determine the prevalence and magnitudes of refractive errors and of parental refraction status in a sample (n=728) of 10- to 18-year-old Austrian grammar school students. Students with myopia or hyperopia were more likely to have ametropic parents and refraction was more myopic in juveniles with one or two parents being ametropic. The prevalence of myopia in children with 2 ametropic parents was 54%, decreasing to 35% in pupils with 1 and to 13% in children with no ametropic parents. The odds ratio for 1 and 2 compared with no ametropic parents was 8.3 and 3.7 for myopia and 1.3 and 1.6 for hyperopia, respectively. Furthermore, the data indicate a stronger influence of the maternal ametropia on children's refractive errors than paternal ametropia. Genetic factors play a significant role in refractive error and may be of dominant influence for school myopia under conditions of low environmental variation.

Operator errors

International Nuclear Information System (INIS)

Knuefer; Lindauer

1980-01-01

Besides that at spectacular events a combination of component failure and human error is often found. Especially the Rasmussen-Report and the German Risk Assessment Study show for pressurised water reactors that human error must not be underestimated. Although operator errors as a form of human error can never be eliminated entirely, they can be minimized and their effects kept within acceptable limits if a thorough training of personnel is combined with an adequate design of the plant against accidents. Contrary to the investigation of engineering errors, the investigation of human errors has so far been carried out with relatively small budgets. Intensified investigations in this field appear to be a worthwhile effort. (orig.)

Practical continuous-variable quantum key distribution without finite sampling bandwidth effects.

Science.gov (United States)

Li, Huasheng; Wang, Chao; Huang, Peng; Huang, Duan; Wang, Tao; Zeng, Guihua

2016-09-05

In a practical continuous-variable quantum key distribution system, finite sampling bandwidth of the employed analog-to-digital converter at the receiver's side may lead to inaccurate results of pulse peak sampling. Then, errors in the parameters estimation resulted. Subsequently, the system performance decreases and security loopholes are exposed to eavesdroppers. In this paper, we propose a novel data acquisition scheme which consists of two parts, i.e., a dynamic delay adjusting module and a statistical power feedback-control algorithm. The proposed scheme may improve dramatically the data acquisition precision of pulse peak sampling and remove the finite sampling bandwidth effects. Moreover, the optimal peak sampling position of a pulse signal can be dynamically calibrated through monitoring the change of the statistical power of the sampled data in the proposed scheme. This helps to resist against some practical attacks, such as the well-known local oscillator calibration attack.

Thermal error analysis and compensation for digital image/volume correlation

Science.gov (United States)

Pan, Bing

2018-02-01

Digital image/volume correlation (DIC/DVC) rely on the digital images acquired by digital cameras and x-ray CT scanners to extract the motion and deformation of test samples. Regrettably, these imaging devices are unstable optical systems, whose imaging geometry may undergo unavoidable slight and continual changes due to self-heating effect or ambient temperature variations. Changes in imaging geometry lead to both shift and expansion in the recorded 2D or 3D images, and finally manifest as systematic displacement and strain errors in DIC/DVC measurements. Since measurement accuracy is always the most important requirement in various experimental mechanics applications, these thermal-induced errors (referred to as thermal errors) should be given serious consideration in order to achieve high accuracy, reproducible DIC/DVC measurements. In this work, theoretical analyses are first given to understand the origin of thermal errors. Then real experiments are conducted to quantify thermal errors. Three solutions are suggested to mitigate or correct thermal errors. Among these solutions, a reference sample compensation approach is highly recommended because of its easy implementation, high accuracy and in-situ error correction capability. Most of the work has appeared in our previously published papers, thus its originality is not claimed. Instead, this paper aims to give a comprehensive overview and more insights of our work on thermal error analysis and compensation for DIC/DVC measurements.

The Attraction Effect Modulates Reward Prediction Errors and Intertemporal Choices.

Science.gov (United States)

Gluth, Sebastian; Hotaling, Jared M; Rieskamp, Jörg

2017-01-11

Classical economic theory contends that the utility of a choice option should be independent of other options. This view is challenged by the attraction effect, in which the relative preference between two options is altered by the addition of a third, asymmetrically dominated option. Here, we leveraged the attraction effect in the context of intertemporal choices to test whether both decisions and reward prediction errors (RPE) in the absence of choice violate the independence of irrelevant alternatives principle. We first demonstrate that intertemporal decision making is prone to the attraction effect in humans. In an independent group of participants, we then investigated how this affects the neural and behavioral valuation of outcomes using a novel intertemporal lottery task and fMRI. Participants' behavioral responses (i.e., satisfaction ratings) were modulated systematically by the attraction effect and this modulation was correlated across participants with the respective change of the RPE signal in the nucleus accumbens. Furthermore, we show that, because exponential and hyperbolic discounting models are unable to account for the attraction effect, recently proposed sequential sampling models might be more appropriate to describe intertemporal choices. Our findings demonstrate for the first time that the attraction effect modulates subjective valuation even in the absence of choice. The findings also challenge the prospect of using neuroscientific methods to measure utility in a context-free manner and have important implications for theories of reinforcement learning and delay discounting. Many theories of value-based decision making assume that people first assess the attractiveness of each option independently of each other and then pick the option with the highest subjective value. The attraction effect, however, shows that adding a new option to a choice set can change the relative value of the existing options, which is a violation of the independence

Dissociable genetic contributions to error processing: a multimodal neuroimaging study.

Directory of Open Access Journals (Sweden)

Yigal Agam

Full Text Available Neuroimaging studies reliably identify two markers of error commission: the error-related negativity (ERN, an event-related potential, and functional MRI activation of the dorsal anterior cingulate cortex (dACC. While theorized to reflect the same neural process, recent evidence suggests that the ERN arises from the posterior cingulate cortex not the dACC. Here, we tested the hypothesis that these two error markers also have different genetic mediation.We measured both error markers in a sample of 92 comprised of healthy individuals and those with diagnoses of schizophrenia, obsessive-compulsive disorder or autism spectrum disorder. Participants performed the same task during functional MRI and simultaneously acquired magnetoencephalography and electroencephalography. We examined the mediation of the error markers by two single nucleotide polymorphisms: dopamine D4 receptor (DRD4 C-521T (rs1800955, which has been associated with the ERN and methylenetetrahydrofolate reductase (MTHFR C677T (rs1801133, which has been associated with error-related dACC activation. We then compared the effects of each polymorphism on the two error markers modeled as a bivariate response.We replicated our previous report of a posterior cingulate source of the ERN in healthy participants in the schizophrenia and obsessive-compulsive disorder groups. The effect of genotype on error markers did not differ significantly by diagnostic group. DRD4 C-521T allele load had a significant linear effect on ERN amplitude, but not on dACC activation, and this difference was significant. MTHFR C677T allele load had a significant linear effect on dACC activation but not ERN amplitude, but the difference in effects on the two error markers was not significant.DRD4 C-521T, but not MTHFR C677T, had a significant differential effect on two canonical error markers. Together with the anatomical dissociation between the ERN and error-related dACC activation, these findings suggest that

Directional dependency of air sampling

International Nuclear Information System (INIS)

1994-01-01

A field study was performed by Idaho State University-Environmental Monitoring Laboratory (EML) to examine the directional dependency of low-volume air samplers. A typical continuous low volume air sampler contains a sample head that is mounted on the sampler housing either horizontally through one of four walls or vertically on an exterior wall 'looking down or up.' In 1992, a field study was undertaken to estimate sampling error and to detect the directional effect of sampler head orientation. Approximately 1/2 mile downwind from a phosphate plant (continuous source of alpha activity), four samplers were positioned in identical orientation alongside one sampler configured with the sample head 'looking down'. At least five consecutive weekly samples were collected. The alpha activity, beta activity, and the Be-7 activity collected on the particulate filter were analyzed to determine sampling error. Four sample heads were than oriented to the four different horizontal directions. Samples were collected for at least five weeks. Analysis of the alpha data can show the effect of sampler orientation to a know near source term. Analysis of the beta and Be-7 activity shows the effect of sampler orientation to a ubiquitous source term

Temperature Dependence of Faraday Effect-Induced Bias Error in a Fiber Optic Gyroscope.

Science.gov (United States)

Li, Xuyou; Liu, Pan; Guang, Xingxing; Xu, Zhenlong; Guan, Lianwu; Li, Guangchun

2017-09-07

Improving the performance of interferometric fiber optic gyroscope (IFOG) in harsh environments, such as magnetic field and temperature field variation, is necessary for its practical applications. This paper presents an investigation of Faraday effect-induced bias error of IFOG under varying temperature. Jones matrix method is utilized to formulize the temperature dependence of Faraday effect-induced bias error. Theoretical results show that the Faraday effect-induced bias error changes with the temperature in the non-skeleton polarization maintaining (PM) fiber coil. This phenomenon is caused by the temperature dependence of linear birefringence and Verdet constant of PM fiber. Particularly, Faraday effect-induced bias errors of two polarizations always have opposite signs that can be compensated optically regardless of the changes of the temperature. Two experiments with a 1000 m non-skeleton PM fiber coil are performed, and the experimental results support these theoretical predictions. This study is promising for improving the bias stability of IFOG.

Effects of error feedback on a nonlinear bistable system with stochastic resonance

International Nuclear Information System (INIS)

Li Jian-Long; Zhou Hui

2012-01-01

In this paper, we discuss the effects of error feedback on the output of a nonlinear bistable system with stochastic resonance. The bit error rate is employed to quantify the performance of the system. The theoretical analysis and the numerical simulation are presented. By investigating the performances of the nonlinear systems with different strengths of error feedback, we argue that the presented system may provide guidance for practical nonlinear signal processing

Effect of neoclassical toroidal viscosity on error-field penetration thresholds in tokamak plasmas.

Science.gov (United States)

Cole, A J; Hegna, C C; Callen, J D

2007-08-10

A model for field-error penetration is developed that includes nonresonant as well as the usual resonant field-error effects. The nonresonant components cause a neoclassical toroidal viscous torque that keeps the plasma rotating at a rate comparable to the ion diamagnetic frequency. The new theory is used to examine resonant error-field penetration threshold scaling in Ohmic tokamak plasmas. Compared to previous theoretical results, we find the plasma is less susceptible to error-field penetration and locking, by a factor that depends on the nonresonant error-field amplitude.

The effects of field errors on low-gain free-electron lasers

International Nuclear Information System (INIS)

Esarey, E.; Tang, C.M.; Marable, W.P.

1991-01-01

This paper reports on the effects of random wiggler magnetic field errors on low-gain free-electron lasers that are examined analytically and numerically through the use of ensemble averaging techniques. Wiggler field errors perturb the electron beam as it propagates and lead to a random walk of the beam centroid δx, variations in the axial beam energy δ γz and deviations in the relative phase of the electrons in the ponderomotive wave δψ. In principle, the random walk may be kept as small as desired through the use of transverse focusing and beam steering. Transverse focusing of the electron beam is shown to be ineffective in reducing the phase deviation. Furthermore, it is shown that beam steering at the wiggler entrance reduces the average phase deviation at the end of the wiggler by 1/3. The effect of the field errors (via the phase deviation) on the gain in the low-gain regime is calculated. To avoid significant reduction in gain it is necessary for the phase deviation to be small compared to 2π. The detrimental effects of wiggler errors on low-gain free-electron lasers may be reduced by arranging the magnet poles in an optimal ordering such that the magnitude of the phase deviation is minimized

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

Science.gov (United States)

Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized

ADC border effect and suppression of quantization error in the digital dynamic measurement

International Nuclear Information System (INIS)

Bai Li-Na; Liu Hai-Dong; Zhou Wei; Zhai Hong-Qi; Cui Zhen-Jian; Zhao Ming-Ying; Gu Xiao-Qian; Liu Bei-Ling; Huang Li-Bei; Zhang Yong

2017-01-01

The digital measurement and processing is an important direction in the measurement and control field. The quantization error widely existing in the digital processing is always the decisive factor that restricts the development and applications of the digital technology. In this paper, we find that the stability of the digital quantization system is obviously better than the quantization resolution. The application of a border effect in the digital quantization can greatly improve the accuracy of digital processing. Its effective precision has nothing to do with the number of quantization bits, which is only related to the stability of the quantization system. The high precision measurement results obtained in the low level quantization system with high sampling rate have an important application value for the progress in the digital measurement and processing field. (paper)

Errors, error detection, error correction and hippocampal-region damage: data and theories.

Science.gov (United States)

MacKay, Donald G; Johnson, Laura W

2013-11-01

This review and perspective article outlines 15 observational constraints on theories of errors, error detection, and error correction, and their relation to hippocampal-region (HR) damage. The core observations come from 10 studies with H.M., an amnesic with cerebellar and HR damage but virtually no neocortical damage. Three studies examined the detection of errors planted in visual scenes (e.g., a bird flying in a fish bowl in a school classroom) and sentences (e.g., I helped themselves to the birthday cake). In all three experiments, H.M. detected reliably fewer errors than carefully matched memory-normal controls. Other studies examined the detection and correction of self-produced errors, with controls for comprehension of the instructions, impaired visual acuity, temporal factors, motoric slowing, forgetting, excessive memory load, lack of motivation, and deficits in visual scanning or attention. In these studies, H.M. corrected reliably fewer errors than memory-normal and cerebellar controls, and his uncorrected errors in speech, object naming, and reading aloud exhibited two consistent features: omission and anomaly. For example, in sentence production tasks, H.M. omitted one or more words in uncorrected encoding errors that rendered his sentences anomalous (incoherent, incomplete, or ungrammatical) reliably more often than controls. Besides explaining these core findings, the theoretical principles discussed here explain H.M.'s retrograde amnesia for once familiar episodic and semantic information; his anterograde amnesia for novel information; his deficits in visual cognition, sentence comprehension, sentence production, sentence reading, and object naming; and effects of aging on his ability to read isolated low frequency words aloud. These theoretical principles also explain a wide range of other data on error detection and correction and generate new predictions for future test. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of systematic phase errors on optimized quantum random-walk search algorithm

International Nuclear Information System (INIS)

Zhang Yu-Chao; Bao Wan-Su; Wang Xiang; Fu Xiang-Qun

2015-01-01

This study investigates the effects of systematic errors in phase inversions on the success rate and number of iterations in the optimized quantum random-walk search algorithm. Using the geometric description of this algorithm, a model of the algorithm with phase errors is established, and the relationship between the success rate of the algorithm, the database size, the number of iterations, and the phase error is determined. For a given database size, we obtain both the maximum success rate of the algorithm and the required number of iterations when phase errors are present in the algorithm. Analyses and numerical simulations show that the optimized quantum random-walk search algorithm is more robust against phase errors than Grover’s algorithm. (paper)

Error-related anterior cingulate cortex activity and the prediction of conscious error awareness

Directory of Open Access Journals (Sweden)

Catherine eOrr

2012-06-01

Full Text Available Research examining the neural mechanisms associated with error awareness has consistently identified dorsal anterior cingulate activity (ACC as necessary but not predictive of conscious error detection. Two recent studies (Steinhauser and Yeung, 2010; Wessel et al. 2011 have found a contrary pattern of greater dorsal ACC activity (in the form of the error-related negativity during detected errors, but suggested that the greater activity may instead reflect task influences (e.g., response conflict, error probability and or individual variability (e.g., statistical power. We re-analyzed fMRI BOLD data from 56 healthy participants who had previously been administered the Error Awareness Task, a motor Go/No-go response inhibition task in which subjects make errors of commission of which they are aware (Aware errors, or unaware (Unaware errors. Consistent with previous data, the activity in a number of cortical regions was predictive of error awareness, including bilateral inferior parietal and insula cortices, however in contrast to previous studies, including our own smaller sample studies using the same task, error-related dorsal ACC activity was significantly greater during aware errors when compared to unaware errors. While the significantly faster RT for aware errors (compared to unaware was consistent with the hypothesis of higher response conflict increasing ACC activity, we could find no relationship between dorsal ACC activity and the error RT difference. The data suggests that individual variability in error awareness is associated with error-related dorsal ACC activity, and therefore this region may be important to conscious error detection, but it remains unclear what task and individual factors influence error awareness.

Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable.

Science.gov (United States)

Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A

2015-03-15

The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.

Effects of digital human-machine interface characteristics on human error in nuclear power plants

International Nuclear Information System (INIS)

Li Pengcheng; Zhang Li; Dai Licao; Huang Weigang

2011-01-01

In order to identify the effects of digital human-machine interface characteristics on human error in nuclear power plants, the new characteristics of digital human-machine interface are identified by comparing with the traditional analog control systems in the aspects of the information display, user interface interaction and management, control systems, alarm systems and procedures system, and the negative effects of digital human-machine interface characteristics on human error are identified by field research and interviewing with operators such as increased cognitive load and workload, mode confusion, loss of situation awareness. As to the adverse effects related above, the corresponding prevention and control measures of human errors are provided to support the prevention and minimization of human errors and the optimization of human-machine interface design. (authors)

[Errors in laboratory daily practice].

Science.gov (United States)

Larrose, C; Le Carrer, D

2007-01-01

Legislation set by GBEA (Guide de bonne exécution des analyses) requires that, before performing analysis, the laboratory directors have to check both the nature of the samples and the patients identity. The data processing of requisition forms, which identifies key errors, was established in 2000 and in 2002 by the specialized biochemistry laboratory, also with the contribution of the reception centre for biological samples. The laboratories follow a strict criteria of defining acceptability as a starting point for the reception to then check requisition forms and biological samples. All errors are logged into the laboratory database and analysis report are sent to the care unit specifying the problems and the consequences they have on the analysis. The data is then assessed by the laboratory directors to produce monthly or annual statistical reports. This indicates the number of errors, which are then indexed to patient files to reveal the specific problem areas, therefore allowing the laboratory directors to teach the nurses and enable corrective action.

Effects and Correction of Closed Orbit Magnet Errors in the SNS Ring

Energy Technology Data Exchange (ETDEWEB)

Bunch, S.C.; Holmes, J.

2004-01-01

We consider the effect and correction of three types of orbit errors in SNS: quadrupole displacement errors, dipole displacement errors, and dipole field errors. Using the ORBIT beam dynamics code, we focus on orbit deflection of a standard pencil beam and on beam losses in a high intensity injection simulation. We study the correction of these orbit errors using the proposed system of 88 (44 horizontal and 44 vertical) ring beam position monitors (BPMs) and 52 (24 horizontal and 28 vertical) dipole corrector magnets. Correction is carried out numerically by adjusting the kick strengths of the dipole corrector magnets to minimize the sum of the squares of the BPM signals for the pencil beam. In addition to using the exact BPM signals as input to the correction algorithm, we also consider the effect of random BPM signal errors. For all three types of error and for perturbations of individual magnets, the correction algorithm always chooses the three-bump method to localize the orbit displacement to the region between the magnet and its adjacent correctors. The values of the BPM signals resulting from specified settings of the dipole corrector kick strengths can be used to set up the orbit response matrix, which can then be applied to the correction in the limit that the signals from the separate errors add linearly. When high intensity calculations are carried out to study beam losses, it is seen that the SNS orbit correction system, even with BPM uncertainties, is sufficient to correct losses to less than 10-4 in nearly all cases, even those for which uncorrected losses constitute a large portion of the beam.

The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model.

Science.gov (United States)

Fritz, Matthew S; Kenny, David A; MacKinnon, David P

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator-to-outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. To explore the combined effect of measurement error and omitted confounders in the same model, the effect of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect.

Statistical theory for estimating sampling errors of regional radiation averages based on satellite measurements

Science.gov (United States)

Smith, G. L.; Bess, T. D.; Minnis, P.

1983-01-01

The processes which determine the weather and climate are driven by the radiation received by the earth and the radiation subsequently emitted. A knowledge of the absorbed and emitted components of radiation is thus fundamental for the study of these processes. In connection with the desire to improve the quality of long-range forecasting, NASA is developing the Earth Radiation Budget Experiment (ERBE), consisting of a three-channel scanning radiometer and a package of nonscanning radiometers. A set of these instruments is to be flown on both the NOAA-F and NOAA-G spacecraft, in sun-synchronous orbits, and on an Earth Radiation Budget Satellite. The purpose of the scanning radiometer is to obtain measurements from which the average reflected solar radiant exitance and the average earth-emitted radiant exitance at a reference level can be established. The estimate of regional average exitance obtained will not exactly equal the true value of the regional average exitance, but will differ due to spatial sampling. A method is presented for evaluating this spatial sampling error.

The dose distribution and DVH change analysis wing to effect of the patient setup error

International Nuclear Information System (INIS)

Kim, Kyung Tae; Ju, Sang Gyu; Ahn, Jae Hong; Park, Young Hwan

2004-01-01

The setup error due to the patient and the staff from radiation treatment as the reason which is important the treatment record could be decided is a possibility of effect. The SET-UP ERROR of the patient analyzes the effect of dose distribution and DVH from radiation treatment of the patient. This test uses human phantom and when C-T scan doing, It rotated the Left direction of the human phantom and it made SET-UP ERROR, Standard plan and 3 mm, 5 mm, 7 mm, 10 mm, 15 mm, 20 mm with to distinguish, it made the C-T scan error. With the result, The SET-UP ERROR got each C-T image Using RTP equipment It used the plan which is used generally from clinical - Box plan, 3 Dimension plan( identical angle 5beam plan) Also, ( CTV+1cm margin, CTV+0.5cm margin, CTV+0.3,cm margin = PTV) it distinguished the standard plan and each set-up error plan and the plan used a dose distribution and the DVH and it analyzed. The Box 4 the plan and 3 Dimension plan which it bites it got similar an dose distribution and DVH in 3 mm, 5 mm From rotation error and Rectilinear movement (0%-2%). Rotation error and rectilinear error 7 mm, 10 mm, 15 mm, 20 mm appeared effect it will go mad to a enough change in treatment (2%-11%) The diminishes the effect of the SET-UP ERROR must reduce move with tension of the patient Also, we are important accessory development and the supply that it reducing of reproducibility and the move.

The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model

Science.gov (United States)

Fritz, Matthew S.; Kenny, David A.; MacKinnon, David P.

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator to outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. In order to explore the combined effect of measurement error and omitted confounders in the same model, the impact of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect. PMID:27739903

Effect of sample size on bias correction performance

Science.gov (United States)

Reiter, Philipp; Gutjahr, Oliver; Schefczyk, Lukas; Heinemann, Günther; Casper, Markus C.

2014-05-01

The output of climate models often shows a bias when compared to observed data, so that a preprocessing is necessary before using it as climate forcing in impact modeling (e.g. hydrology, species distribution). A common bias correction method is the quantile matching approach, which adapts the cumulative distribution function of the model output to the one of the observed data by means of a transfer function. Especially for precipitation we expect the bias correction performance to strongly depend on sample size, i.e. the length of the period used for calibration of the transfer function. We carry out experiments using the precipitation output of ten regional climate model (RCM) hindcast runs from the EU-ENSEMBLES project and the E-OBS observational dataset for the period 1961 to 2000. The 40 years are split into a 30 year calibration period and a 10 year validation period. In the first step, for each RCM transfer functions are set up cell-by-cell, using the complete 30 year calibration period. The derived transfer functions are applied to the validation period of the respective RCM precipitation output and the mean absolute errors in reference to the observational dataset are calculated. These values are treated as "best fit" for the respective RCM. In the next step, this procedure is redone using subperiods out of the 30 year calibration period. The lengths of these subperiods are reduced from 29 years down to a minimum of 1 year, only considering subperiods of consecutive years. This leads to an increasing number of repetitions for smaller sample sizes (e.g. 2 for a length of 29 years). In the last step, the mean absolute errors are statistically tested against the "best fit" of the respective RCM to compare the performances. In order to analyze if the intensity of the effect of sample size depends on the chosen correction method, four variations of the quantile matching approach (PTF, QUANT/eQM, gQM, GQM) are applied in this study. The experiments are further

Counting OCR errors in typeset text

Science.gov (United States)

Sandberg, Jonathan S.

1995-03-01

Frequently object recognition accuracy is a key component in the performance analysis of pattern matching systems. In the past three years, the results of numerous excellent and rigorous studies of OCR system typeset-character accuracy (henceforth OCR accuracy) have been published, encouraging performance comparisons between a variety of OCR products and technologies. These published figures are important; OCR vendor advertisements in the popular trade magazines lead readers to believe that published OCR accuracy figures effect market share in the lucrative OCR market. Curiously, a detailed review of many of these OCR error occurrence counting results reveals that they are not reproducible as published and they are not strictly comparable due to larger variances in the counts than would be expected by the sampling variance. Naturally, since OCR accuracy is based on a ratio of the number of OCR errors over the size of the text searched for errors, imprecise OCR error accounting leads to similar imprecision in OCR accuracy. Some published papers use informal, non-automatic, or intuitively correct OCR error accounting. Still other published results present OCR error accounting methods based on string matching algorithms such as dynamic programming using Levenshtein (edit) distance but omit critical implementation details (such as the existence of suspect markers in the OCR generated output or the weights used in the dynamic programming minimization procedure). The problem with not specifically revealing the accounting method is that the number of errors found by different methods are significantly different. This paper identifies the basic accounting methods used to measure OCR errors in typeset text and offers an evaluation and comparison of the various accounting methods.

Adaptive control of theophylline therapy: importance of blood sampling times.

Science.gov (United States)

D'Argenio, D Z; Khakmahd, K

1983-10-01

A two-observation protocol for estimating theophylline clearance during a constant-rate intravenous infusion is used to examine the importance of blood sampling schedules with regard to the information content of resulting concentration data. Guided by a theory for calculating maximally informative sample times, population simulations are used to assess the effect of specific sampling times on the precision of resulting clearance estimates and subsequent predictions of theophylline plasma concentrations. The simulations incorporated noise terms for intersubject variability, dosing errors, sample collection errors, and assay error. Clearance was estimated using Chiou's method, least squares, and a Bayesian estimation procedure. The results of these simulations suggest that clinically significant estimation and prediction errors may result when using the above two-point protocol for estimating theophylline clearance if the time separating the two blood samples is less than one population mean elimination half-life.

Errors and Understanding: The Effects of Error-Management Training on Creative Problem-Solving

Science.gov (United States)

Robledo, Issac C.; Hester, Kimberly S.; Peterson, David R.; Barrett, Jamie D.; Day, Eric A.; Hougen, Dean P.; Mumford, Michael D.

2012-01-01

People make errors in their creative problem-solving efforts. The intent of this article was to assess whether error-management training would improve performance on creative problem-solving tasks. Undergraduates were asked to solve an educational leadership problem known to call for creative thought where problem solutions were scored for…

Small Body GN and C Research Report: G-SAMPLE - An In-Flight Dynamical Method for Identifying Sample Mass [External Release Version

Science.gov (United States)

Carson, John M., III; Bayard, David S.

2006-01-01

G-SAMPLE is an in-flight dynamical method for use by sample collection missions to identify the presence and quantity of collected sample material. The G-SAMPLE method implements a maximum-likelihood estimator to identify the collected sample mass, based on onboard force sensor measurements, thruster firings, and a dynamics model of the spacecraft. With G-SAMPLE, sample mass identification becomes a computation rather than an extra hardware requirement; the added cost of cameras or other sensors for sample mass detection is avoided. Realistic simulation examples are provided for a spacecraft configuration with a sample collection device mounted on the end of an extended boom. In one representative example, a 1000 gram sample mass is estimated to within 110 grams (95% confidence) under realistic assumptions of thruster profile error, spacecraft parameter uncertainty, and sensor noise. For convenience to future mission design, an overall sample-mass estimation error budget is developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

Outlier Removal and the Relation with Reporting Errors and Quality of Psychological Research

Science.gov (United States)

Bakker, Marjan; Wicherts, Jelte M.

2014-01-01

Background The removal of outliers to acquire a significant result is a questionable research practice that appears to be commonly used in psychology. In this study, we investigated whether the removal of outliers in psychology papers is related to weaker evidence (against the null hypothesis of no effect), a higher prevalence of reporting errors, and smaller sample sizes in these papers compared to papers in the same journals that did not report the exclusion of outliers from the analyses. Methods and Findings We retrieved a total of 2667 statistical results of null hypothesis significance tests from 153 articles in main psychology journals, and compared results from articles in which outliers were removed (N = 92) with results from articles that reported no exclusion of outliers (N = 61). We preregistered our hypotheses and methods and analyzed the data at the level of articles. Results show no significant difference between the two types of articles in median p value, sample sizes, or prevalence of all reporting errors, large reporting errors, and reporting errors that concerned the statistical significance. However, we did find a discrepancy between the reported degrees of freedom of t tests and the reported sample size in 41% of articles that did not report removal of any data values. This suggests common failure to report data exclusions (or missingness) in psychological articles. Conclusions We failed to find that the removal of outliers from the analysis in psychological articles was related to weaker evidence (against the null hypothesis of no effect), sample size, or the prevalence of errors. However, our control sample might be contaminated due to nondisclosure of excluded values in articles that did not report exclusion of outliers. Results therefore highlight the importance of more transparent reporting of statistical analyses. PMID:25072606

Quantum tomography via compressed sensing: error bounds, sample complexity and efficient estimators

International Nuclear Information System (INIS)

Flammia, Steven T; Gross, David; Liu, Yi-Kai; Eisert, Jens

2012-01-01

Intuitively, if a density operator has small rank, then it should be easier to estimate from experimental data, since in this case only a few eigenvectors need to be learned. We prove two complementary results that confirm this intuition. Firstly, we show that a low-rank density matrix can be estimated using fewer copies of the state, i.e. the sample complexity of tomography decreases with the rank. Secondly, we show that unknown low-rank states can be reconstructed from an incomplete set of measurements, using techniques from compressed sensing and matrix completion. These techniques use simple Pauli measurements, and their output can be certified without making any assumptions about the unknown state. In this paper, we present a new theoretical analysis of compressed tomography, based on the restricted isometry property for low-rank matrices. Using these tools, we obtain near-optimal error bounds for the realistic situation where the data contain noise due to finite statistics, and the density matrix is full-rank with decaying eigenvalues. We also obtain upper bounds on the sample complexity of compressed tomography, and almost-matching lower bounds on the sample complexity of any procedure using adaptive sequences of Pauli measurements. Using numerical simulations, we compare the performance of two compressed sensing estimators—the matrix Dantzig selector and the matrix Lasso—with standard maximum-likelihood estimation (MLE). We find that, given comparable experimental resources, the compressed sensing estimators consistently produce higher fidelity state reconstructions than MLE. In addition, the use of an incomplete set of measurements leads to faster classical processing with no loss of accuracy. Finally, we show how to certify the accuracy of a low-rank estimate using direct fidelity estimation, and describe a method for compressed quantum process tomography that works for processes with small Kraus rank and requires only Pauli eigenstate preparations

Field testing for cosmic ray soft errors in semiconductor memories

International Nuclear Information System (INIS)

O'Gorman, T.J.; Ross, J.M.; Taber, A.H.; Ziegler, J.F.; Muhlfeld, H.P.; Montrose, C.J.; Curtis, H.W.; Walsh, J.L.

1996-01-01

This paper presents a review of experiments performed by IBM to investigate the causes of soft errors in semiconductor memory chips under field test conditions. The effects of alpha-particles and cosmic rays are separated by comparing multiple measurements of the soft-error rate (SER) of samples of memory chips deep underground and at various altitudes above the earth. The results of case studies on four different memory chips show that cosmic rays are an important source of the ionizing radiation that causes soft errors. The results of field testing are used to confirm the accuracy of the modeling and the accelerated testing of chips

The effects of road traffic noise on the students\\' errors in movement time anticipation; the role of introversion

Directory of Open Access Journals (Sweden)

I Alimohammadi

2012-12-01

Full Text Available   Background and Aims: Traffic noise is one of the most important urban noise pollution, which causes various physical and mental effects, impairment in daily activities, sleep disturbances, hearing loss and the impact on job performance. Thus it can reduce concentration significantly and increase the rate of traffic accidents. Some individual differences such as personality types in noise effects, affect.   Methods : Traffic noise has been measured and recorded in 10 arterial streets in Tehran, and the average sound pressure level measured was72/9 dB during two hours played for participants in the acousticroom . The sample size consisted of 80 patients (40 cases and 40 controls who were students of Tehran University of Medical Sciences. Personality type was determined by using Eysenc’s Personality Inventory (EPIquestionnaire. The error time movement anticipation before and after exposure to traffic noisewas measured by ZBA computerize test.   Results: The results revealed that error time movement anticipation before exposure to traffic noise have significant difference for introverts and extraverts Introverts have less errortime movement anticipation than extroversion ,whereas extroverts have less error time movement anticipation that introversion after exposure to traffic noise.   Conclusion: According to the obtained results, noise created different effects on the performance of personality type. Extroverts may be expected to adapt better to noise during mental performance, compared to people with opposite personality traits.  

Field error lottery

Energy Technology Data Exchange (ETDEWEB)

Elliott, C.J.; McVey, B. (Los Alamos National Lab., NM (USA)); Quimby, D.C. (Spectra Technology, Inc., Bellevue, WA (USA))

1990-01-01

The level of field errors in an FEL is an important determinant of its performance. We have computed 3D performance of a large laser subsystem subjected to field errors of various types. These calculations have been guided by simple models such as SWOOP. The technique of choice is utilization of the FELEX free electron laser code that now possesses extensive engineering capabilities. Modeling includes the ability to establish tolerances of various types: fast and slow scale field bowing, field error level, beam position monitor error level, gap errors, defocusing errors, energy slew, displacement and pointing errors. Many effects of these errors on relative gain and relative power extraction are displayed and are the essential elements of determining an error budget. The random errors also depend on the particular random number seed used in the calculation. The simultaneous display of the performance versus error level of cases with multiple seeds illustrates the variations attributable to stochasticity of this model. All these errors are evaluated numerically for comprehensive engineering of the system. In particular, gap errors are found to place requirements beyond mechanical tolerances of {plus minus}25{mu}m, and amelioration of these may occur by a procedure utilizing direct measurement of the magnetic fields at assembly time. 4 refs., 12 figs.

A Research on the Responsibility of Accounting Professionals to Determine and Prevent Accounting Errors and Frauds: Edirne Sample

Directory of Open Access Journals (Sweden)

Semanur Adalı

2017-09-01

Full Text Available In this study, the ethical dimensions of accounting professionals related to accounting errors and frauds were examined. Firstly, general and technical information about accounting were provided. Then, some terminology on error, fraud and ethics in accounting were discussed. Study also included recent statistics about accounting errors and fraud as well as presenting a literature review. As the methodology of research, a questionnaire was distributed to 36 accounting professionals residing in Edirne city of Turkey. The collected data were then entered to the SPSS package program for analysis. The study revealed very important results. Accounting professionals think that, accounting chambers do not organize enough seminars/conferences on errors and fraud. They also believe that supervision and disciplinary boards of professional accounting chambers fulfill their responsibilities partially. Attitude of professional accounting chambers in terms of errors, fraud and ethics is considered neither strict nor lenient. But, most accounting professionals are aware of colleagues who had disciplinary penalties. Most important and effective tool to prevent errors and fraud is indicated as external audit, but internal audit and internal control are valued as well. According to accounting professionals, most errors occur due to incorrect data received from clients and as a result of recording. Fraud is generally made in order to get credit from banks and for providing benefits to the organization by not showing the real situation of the firm. Finally, accounting professionals state that being honest, trustworthy and impartial is the basis of accounting profession and accountants must adhere to ethical rules.

Metacognitive Unawareness of the Errorful Generation Benefit and Its Effects on Self-Regulated Learning

Science.gov (United States)

Yang, Chunliang; Potts, Rosalind; Shanks, David R.

2017-01-01

Generating errors followed by corrective feedback enhances retention more effectively than does reading--the benefit of errorful generation--but people tend to be unaware of this benefit. The current research explored this metacognitive unawareness, its effect on self-regulated learning, and how to alleviate or reverse it. People's beliefs about…

Incorporating measurement error in n = 1 psychological autoregressive modeling

Science.gov (United States)

Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988

Effects of structural error on the estimates of parameters of dynamical systems

Science.gov (United States)

Hadaegh, F. Y.; Bekey, G. A.

1986-01-01

In this paper, the notion of 'near-equivalence in probability' is introduced for identifying a system in the presence of several error sources. Following some basic definitions, necessary and sufficient conditions for the identifiability of parameters are given. The effects of structural error on the parameter estimates for both the deterministic and stochastic cases are considered.

The effects of error augmentation on learning to walk on a narrow balance beam.

Science.gov (United States)

Domingo, Antoinette; Ferris, Daniel P

2010-10-01

Error augmentation during training has been proposed as a means to facilitate motor learning due to the human nervous system's reliance on performance errors to shape motor commands. We studied the effects of error augmentation on short-term learning of walking on a balance beam to determine whether it had beneficial effects on motor performance. Four groups of able-bodied subjects walked on a treadmill-mounted balance beam (2.5-cm wide) before and after 30 min of training. During training, two groups walked on the beam with a destabilization device that augmented error (Medium and High Destabilization groups). A third group walked on a narrower beam (1.27-cm) to augment error (Narrow). The fourth group practiced walking on the 2.5-cm balance beam (Wide). Subjects in the Wide group had significantly greater improvements after training than the error augmentation groups. The High Destabilization group had significantly less performance gains than the Narrow group in spite of similar failures per minute during training. In a follow-up experiment, a fifth group of subjects (Assisted) practiced with a device that greatly reduced catastrophic errors (i.e., stepping off the beam) but maintained similar pelvic movement variability. Performance gains were significantly greater in the Wide group than the Assisted group, indicating that catastrophic errors were important for short-term learning. We conclude that increasing errors during practice via destabilization and a narrower balance beam did not improve short-term learning of beam walking. In addition, the presence of qualitatively catastrophic errors seems to improve short-term learning of walking balance.

Galaxy Cluster Shapes and Systematic Errors in the Hubble Constant as Determined by the Sunyaev-Zel'dovich Effect

Science.gov (United States)

Sulkanen, Martin E.; Joy, M. K.; Patel, S. K.

1998-01-01

Imaging of the Sunyaev-Zei'dovich (S-Z) effect in galaxy clusters combined with the cluster plasma x-ray diagnostics can measure the cosmic distance scale to high accuracy. However, projecting the inverse-Compton scattering and x-ray emission along the cluster line-of-sight will introduce systematic errors in the Hubble constant, H$-O$, because the true shape of the cluster is not known. This effect remains present for clusters that are otherwise chosen to avoid complications for the S-Z and x-ray analysis, such as plasma temperature variations, cluster substructure, or cluster dynamical evolution. In this paper we present a study of the systematic errors in the value of H$-0$, as determined by the x-ray and S-Z properties of a theoretical sample of triaxial isothermal 'beta-model' clusters, caused by projection effects and observer orientation relative to the model clusters' principal axes. The model clusters are not generated as ellipsoids of rotation, but have three independent 'core radii', as well as a random orientation to the plane of the sky.

The effect of monetary punishment on error evaluation in a Go/No-go task.

Science.gov (United States)

Maruo, Yuya; Sommer, Werner; Masaki, Hiroaki

2017-10-01

Little is known about the effects of the motivational significance of errors in Go/No-go tasks. We investigated the impact of monetary punishment on the error-related negativity (ERN) and error positivity (Pe) for both overt errors and partial errors, that is, no-go trials without overt responses but with covert muscle activities. We compared high and low punishment conditions where errors were penalized with 50 or 5 yen, respectively, and a control condition without monetary consequences for errors. Because we hypothesized that the partial-error ERN might overlap with the no-go N2, we compared ERPs between correct rejections (i.e., successful no-go trials) and partial errors in no-go trials. We also expected that Pe amplitudes should increase with the severity of the penalty for errors. Mean error rates were significantly lower in the high punishment than in the control condition. Monetary punishment did not influence the overt-error ERN and partial-error ERN in no-go trials. The ERN in no-go trials did not differ between partial errors and overt errors; in addition, ERPs for correct rejections in no-go trials without partial errors were of the same size as in go-trial. Therefore the overt-error ERN and the partial-error ERN may share similar error monitoring processes. Monetary punishment increased Pe amplitudes for overt errors, suggesting enhanced error evaluation processes. For partial errors an early Pe was observed, presumably representing inhibition processes. Interestingly, even partial errors elicited the Pe, suggesting that covert erroneous activities could be detected in Go/No-go tasks. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

Directory of Open Access Journals (Sweden)

Yun Shi

2014-01-01

Full Text Available Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM.

Magnetic Nanoparticle Thermometer: An Investigation of Minimum Error Transmission Path and AC Bias Error

Directory of Open Access Journals (Sweden)

Zhongzhou Du

2015-04-01

Full Text Available The signal transmission module of a magnetic nanoparticle thermometer (MNPT was established in this study to analyze the error sources introduced during the signal flow in the hardware system. The underlying error sources that significantly affected the precision of the MNPT were determined through mathematical modeling and simulation. A transfer module path with the minimum error in the hardware system was then proposed through the analysis of the variations of the system error caused by the significant error sources when the signal flew through the signal transmission module. In addition, a system parameter, named the signal-to-AC bias ratio (i.e., the ratio between the signal and AC bias, was identified as a direct determinant of the precision of the measured temperature. The temperature error was below 0.1 K when the signal-to-AC bias ratio was higher than 80 dB, and other system errors were not considered. The temperature error was below 0.1 K in the experiments with a commercial magnetic fluid (Sample SOR-10, Ocean Nanotechnology, Springdale, AR, USA when the hardware system of the MNPT was designed with the aforementioned method.

Error Estimates for the Approximation of the Effective Hamiltonian

International Nuclear Information System (INIS)

Camilli, Fabio; Capuzzo Dolcetta, Italo; Gomes, Diogo A.

2008-01-01

We study approximation schemes for the cell problem arising in homogenization of Hamilton-Jacobi equations. We prove several error estimates concerning the rate of convergence of the approximation scheme to the effective Hamiltonian, both in the optimal control setting and as well as in the calculus of variations setting

On the effect of systematic errors in near real time accountancy

International Nuclear Information System (INIS)

Avenhaus, R.

1987-01-01

Systematic measurement errors have a decisive impact on nuclear materials accountancy. This has been demonstrated at various occasions for a fixed number of inventory periods, i.e. for situations where the overall probability of detection is taken as the measure of effectiveness. In the framework of Near Real Time Accountancy (NRTA), however, such analyses have not yet been performed. In this paper sequential test procedures are considered which are based on the so-called MUF-Residuals. It is shown that, if the decision maker does not know the systematic error variance, the average run lengths tend towards infinity if this variance is equal or longer than that of the random error. Furthermore, if the decision maker knows this invariance, the average run length for constant loss or diversion is not shorter than that without loss or diversion. These results cast some doubt on the present practice of data evaluation where systematic errors are tacitly assumed to persist for an infinite time. In fact, information about the time dependence of the variances of these errors has to be gathered in order that the efficiency of NRTA evaluation methods can be estimated realistically

Quality assurance and human error effects on the structural safety

International Nuclear Information System (INIS)

Bertero, R.; Lopez, R.; Sarrate, M.

1991-01-01

Statistical surveys show that the frequency of failure of structures is much larger than that expected by the codes. Evidence exists that human errors (especially during the design process) is the main cause for the difference between the failure probability admitted by codes and the reality. In this paper, the attenuation of human error effects using tools of quality assurance is analyzed. In particular, the importance of the independent design review is highlighted, and different approaches are discussed. The experience from the Atucha II project, as well as the USA and German practice on independent design review, are summarized. (Author)

The Effect of Type-1 Error on Deterrence

DEFF Research Database (Denmark)

Lando, Henrik; Mungan, Murat C.

2018-01-01

According to a conventional view, type-1 error (wrongful conviction) is as detrimental to deterrence as type-2 error (wrongful acquittal), because type-1 error lowers the pay-off from acting within the law. This view has led to the claim that the pro-defendant bias of criminal procedure, and its ...

Minimizing treatment planning errors in proton therapy using failure mode and effects analysis

Energy Technology Data Exchange (ETDEWEB)

Zheng, Yuanshui, E-mail: yuanshui.zheng@okc.procure.com [ProCure Proton Therapy Center, 5901 W Memorial Road, Oklahoma City, Oklahoma 73142 and Department of Physics, Oklahoma State University, Stillwater, Oklahoma 74078-3072 (United States); Johnson, Randall; Larson, Gary [ProCure Proton Therapy Center, 5901 W Memorial Road, Oklahoma City, Oklahoma 73142 (United States)

2016-06-15

Purpose: Failure mode and effects analysis (FMEA) is a widely used tool to evaluate safety or reliability in conventional photon radiation therapy. However, reports about FMEA application in proton therapy are scarce. The purpose of this study is to apply FMEA in safety improvement of proton treatment planning at their center. Methods: The authors performed an FMEA analysis of their proton therapy treatment planning process using uniform scanning proton beams. The authors identified possible failure modes in various planning processes, including image fusion, contouring, beam arrangement, dose calculation, plan export, documents, billing, and so on. For each error, the authors estimated the frequency of occurrence, the likelihood of being undetected, and the severity of the error if it went undetected and calculated the risk priority number (RPN). The FMEA results were used to design their quality management program. In addition, the authors created a database to track the identified dosimetric errors. Periodically, the authors reevaluated the risk of errors by reviewing the internal error database and improved their quality assurance program as needed. Results: In total, the authors identified over 36 possible treatment planning related failure modes and estimated the associated occurrence, detectability, and severity to calculate the overall risk priority number. Based on the FMEA, the authors implemented various safety improvement procedures into their practice, such as education, peer review, and automatic check tools. The ongoing error tracking database provided realistic data on the frequency of occurrence with which to reevaluate the RPNs for various failure modes. Conclusions: The FMEA technique provides a systematic method for identifying and evaluating potential errors in proton treatment planning before they result in an error in patient dose delivery. The application of FMEA framework and the implementation of an ongoing error tracking system at their

Minimizing treatment planning errors in proton therapy using failure mode and effects analysis

International Nuclear Information System (INIS)

Zheng, Yuanshui; Johnson, Randall; Larson, Gary

2016-01-01

Purpose: Failure mode and effects analysis (FMEA) is a widely used tool to evaluate safety or reliability in conventional photon radiation therapy. However, reports about FMEA application in proton therapy are scarce. The purpose of this study is to apply FMEA in safety improvement of proton treatment planning at their center. Methods: The authors performed an FMEA analysis of their proton therapy treatment planning process using uniform scanning proton beams. The authors identified possible failure modes in various planning processes, including image fusion, contouring, beam arrangement, dose calculation, plan export, documents, billing, and so on. For each error, the authors estimated the frequency of occurrence, the likelihood of being undetected, and the severity of the error if it went undetected and calculated the risk priority number (RPN). The FMEA results were used to design their quality management program. In addition, the authors created a database to track the identified dosimetric errors. Periodically, the authors reevaluated the risk of errors by reviewing the internal error database and improved their quality assurance program as needed. Results: In total, the authors identified over 36 possible treatment planning related failure modes and estimated the associated occurrence, detectability, and severity to calculate the overall risk priority number. Based on the FMEA, the authors implemented various safety improvement procedures into their practice, such as education, peer review, and automatic check tools. The ongoing error tracking database provided realistic data on the frequency of occurrence with which to reevaluate the RPNs for various failure modes. Conclusions: The FMEA technique provides a systematic method for identifying and evaluating potential errors in proton treatment planning before they result in an error in patient dose delivery. The application of FMEA framework and the implementation of an ongoing error tracking system at their

Effect of Numerical Error on Gravity Field Estimation for GRACE and Future Gravity Missions

Science.gov (United States)

McCullough, Christopher; Bettadpur, Srinivas

2015-04-01

In recent decades, gravity field determination from low Earth orbiting satellites, such as the Gravity Recovery and Climate Experiment (GRACE), has become increasingly more effective due to the incorporation of high accuracy measurement devices. Since instrumentation quality will only increase in the near future and the gravity field determination process is computationally and numerically intensive, numerical error from the use of double precision arithmetic will eventually become a prominent error source. While using double-extended or quadruple precision arithmetic will reduce these errors, the numerical limitations of current orbit determination algorithms and processes must be accurately identified and quantified in order to adequately inform the science data processing techniques of future gravity missions. The most obvious numerical limitation in the orbit determination process is evident in the comparison of measured observables with computed values, derived from mathematical models relating the satellites' numerically integrated state to the observable. Significant error in the computed trajectory will corrupt this comparison and induce error in the least squares solution of the gravitational field. In addition, errors in the numerically computed trajectory propagate into the evaluation of the mathematical measurement model's partial derivatives. These errors amalgamate in turn with numerical error from the computation of the state transition matrix, computed using the variational equations of motion, in the least squares mapping matrix. Finally, the solution of the linearized least squares system, computed using a QR factorization, is also susceptible to numerical error. Certain interesting combinations of each of these numerical errors are examined in the framework of GRACE gravity field determination to analyze and quantify their effects on gravity field recovery.

Effects of hemisphere speech dominance and seizure focus on patterns of behavioral response errors for three types of stimuli.

Science.gov (United States)

Rausch, R; MacDonald, K

1997-03-01

We used a protocol consisting of a continuous presentation of stimuli with associated response requests during an intracarotid sodium amobarbital procedure (IAP) to study the effects of hemisphere injected (speech dominant vs. nondominant) and seizure focus (left temporal lobe vs. right temporal lobe) on the pattern of behavioral response errors for three types of visual stimuli (pictures of common objects, words, and abstract forms). Injection of the left speech dominant hemisphere compared to the right nondominant hemisphere increased overall errors and affected the pattern of behavioral errors. The presence of a seizure focus in the contralateral hemisphere increased overall errors, particularly for the right temporal lobe seizure patients, but did not affect the pattern of behavioral errors. Left hemisphere injections disrupted both naming and reading responses at a rate similar to that of matching-to-sample performance. Also, a short-term memory deficit was observed with all three stimuli. Long-term memory testing following the left hemisphere injection indicated that only for pictures of common objects were there fewer errors during the early postinjection period than for the later long-term memory testing. Therefore, despite the inability to respond to picture stimuli, picture items, but not words or forms, could be sufficiently encoded for later recall. In contrast, right hemisphere injections resulted in few errors, with a pattern suggesting a mild general cognitive decrease. A selective weakness in learning unfamiliar forms was found. Our findings indicate that different patterns of behavioral deficits occur following the left vs. right hemisphere injections, with selective patterns specific to stimulus type.

Effects of errors on the dynamic aperture of the Advanced Photon Source storage ring

International Nuclear Information System (INIS)

Bizek, H.; Crosbie, E.; Lessner, E.; Teng, L.; Wirsbinski, J.

1991-01-01

The individual tolerance limits for alignment errors and magnet fabrication errors in the 7-GeV Advanced Photon Source storage ring are determined by computer-simulated tracking. Limits are established for dipole strength and roll errors, quadrupole strength and alignment errors, sextupole strength and alignment errors, as well as higher order multipole strengths in dipole and quadrupole magnets. The effects of girder misalignments on the dynamic aperture are also studied. Computer simulations are obtained with the tracking program RACETRACK, with errors introduced from a user-defined Gaussian distribution, truncated at ±5 standard deviation units. For each error, the average and rms spread of the stable amplitudes are determined for ten distinct machines, defined as ten different seeds to the random distribution, and for five distinct initial directions of the tracking particle. 4 refs., 4 figs., 1 tab

Measurement of peak impact loads differ between accelerometers - Effects of system operating range and sampling rate.

Science.gov (United States)

Ziebart, Christina; Giangregorio, Lora M; Gibbs, Jenna C; Levine, Iris C; Tung, James; Laing, Andrew C

2017-06-14

A wide variety of accelerometer systems, with differing sensor characteristics, are used to detect impact loading during physical activities. The study examined the effects of system characteristics on measured peak impact loading during a variety of activities by comparing outputs from three separate accelerometer systems, and by assessing the influence of simulated reductions in operating range and sampling rate. Twelve healthy young adults performed seven tasks (vertical jump, box drop, heel drop, and bilateral single leg and lateral jumps) while simultaneously wearing three tri-axial accelerometers including a criterion standard laboratory-grade unit (Endevco 7267A) and two systems primarily used for activity-monitoring (ActiGraph GT3X+, GCDC X6-2mini). Peak acceleration (gmax) was compared across accelerometers, and errors resulting from down-sampling (from 640 to 100Hz) and range-limiting (to ±6g) the criterion standard output were characterized. The Actigraph activity-monitoring accelerometer underestimated gmax by an average of 30.2%; underestimation by the X6-2mini was not significant. Underestimation error was greater for tasks with greater impact magnitudes. gmax was underestimated when the criterion standard signal was down-sampled (by an average of 11%), range limited (by 11%), and by combined down-sampling and range-limiting (by 18%). These effects explained 89% of the variance in gmax error for the Actigraph system. This study illustrates that both the type and intensity of activity should be considered when selecting an accelerometer for characterizing impact events. In addition, caution may be warranted when comparing impact magnitudes from studies that use different accelerometers, and when comparing accelerometer outputs to osteogenic impact thresholds proposed in literature. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Error evaluation method for material accountancy measurement. Evaluation of random and systematic errors based on material accountancy data

International Nuclear Information System (INIS)

Nidaira, Kazuo

2008-01-01

International Target Values (ITV) shows random and systematic measurement uncertainty components as a reference for routinely achievable measurement quality in the accountancy measurement. The measurement uncertainty, called error henceforth, needs to be periodically evaluated and checked against ITV for consistency as the error varies according to measurement methods, instruments, operators, certified reference samples, frequency of calibration, and so on. In the paper an error evaluation method was developed with focuses on (1) Specifying clearly error calculation model, (2) Getting always positive random and systematic error variances, (3) Obtaining probability density distribution of an error variance and (4) Confirming the evaluation method by simulation. In addition the method was demonstrated by applying real data. (author)

A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE.

Directory of Open Access Journals (Sweden)

Kevin P Keegan

Full Text Available We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation, to assess sequencing quality (alternatively referred to as "noise" or "error" within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred. Here, DRISEE is applied to (non amplicon data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs, a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms.

Efficient sampling techniques for uncertainty quantification in history matching using nonlinear error models and ensemble level upscaling techniques

KAUST Repository

Efendiev, Y.

2009-11-01

The Markov chain Monte Carlo (MCMC) is a rigorous sampling method to quantify uncertainty in subsurface characterization. However, the MCMC usually requires many flow and transport simulations in evaluating the posterior distribution and can be computationally expensive for fine-scale geological models. We propose a methodology that combines coarse- and fine-scale information to improve the efficiency of MCMC methods. The proposed method employs off-line computations for modeling the relation between coarse- and fine-scale error responses. This relation is modeled using nonlinear functions with prescribed error precisions which are used in efficient sampling within the MCMC framework. We propose a two-stage MCMC where inexpensive coarse-scale simulations are performed to determine whether or not to run the fine-scale (resolved) simulations. The latter is determined on the basis of a statistical model developed off line. The proposed method is an extension of the approaches considered earlier where linear relations are used for modeling the response between coarse-scale and fine-scale models. The approach considered here does not rely on the proximity of approximate and resolved models and can employ much coarser and more inexpensive models to guide the fine-scale simulations. Numerical results for three-phase flow and transport demonstrate the advantages, efficiency, and utility of the method for uncertainty assessment in the history matching. Copyright 2009 by the American Geophysical Union.

Brain negativity as an indicator of predictive error processing: the contribution of visual action effect monitoring.

Science.gov (United States)

Joch, Michael; Hegele, Mathias; Maurer, Heiko; Müller, Hermann; Maurer, Lisa Katharina

2017-07-01

The error (related) negativity (Ne/ERN) is an event-related potential in the electroencephalogram (EEG) correlating with error processing. Its conditions of appearance before terminal external error information suggest that the Ne/ERN is indicative of predictive processes in the evaluation of errors. The aim of the present study was to specifically examine the Ne/ERN in a complex motor task and to particularly rule out other explaining sources of the Ne/ERN aside from error prediction processes. To this end, we focused on the dependency of the Ne/ERN on visual monitoring about the action outcome after movement termination but before result feedback (action effect monitoring). Participants performed a semi-virtual throwing task by using a manipulandum to throw a virtual ball displayed on a computer screen to hit a target object. Visual feedback about the ball flying to the target was masked to prevent action effect monitoring. Participants received a static feedback about the action outcome (850 ms) after each trial. We found a significant negative deflection in the average EEG curves of the error trials peaking at ~250 ms after ball release, i.e., before error feedback. Furthermore, this Ne/ERN signal did not depend on visual ball-flight monitoring after release. We conclude that the Ne/ERN has the potential to indicate error prediction in motor tasks and that it exists even in the absence of action effect monitoring. NEW & NOTEWORTHY In this study, we are separating different kinds of possible contributors to an electroencephalogram (EEG) error correlate (Ne/ERN) in a throwing task. We tested the influence of action effect monitoring on the Ne/ERN amplitude in the EEG. We used a task that allows us to restrict movement correction and action effect monitoring and to control the onset of result feedback. We ascribe the Ne/ERN to predictive error processing where a conscious feeling of failure is not a prerequisite. Copyright © 2017 the American Physiological

Effect of patient setup errors on simultaneously integrated boost head and neck IMRT treatment plans

International Nuclear Information System (INIS)

Siebers, Jeffrey V.; Keall, Paul J.; Wu Qiuwen; Williamson, Jeffrey F.; Schmidt-Ullrich, Rupert K.

2005-01-01

Purpose: The purpose of this study is to determine dose delivery errors that could result from random and systematic setup errors for head-and-neck patients treated using the simultaneous integrated boost (SIB)-intensity-modulated radiation therapy (IMRT) technique. Methods and Materials: Twenty-four patients who participated in an intramural Phase I/II parotid-sparing IMRT dose-escalation protocol using the SIB treatment technique had their dose distributions reevaluated to assess the impact of random and systematic setup errors. The dosimetric effect of random setup error was simulated by convolving the two-dimensional fluence distribution of each beam with the random setup error probability density distribution. Random setup errors of σ = 1, 3, and 5 mm were simulated. Systematic setup errors were simulated by randomly shifting the patient isocenter along each of the three Cartesian axes, with each shift selected from a normal distribution. Systematic setup error distributions with Σ = 1.5 and 3.0 mm along each axis were simulated. Combined systematic and random setup errors were simulated for σ = Σ = 1.5 and 3.0 mm along each axis. For each dose calculation, the gross tumor volume (GTV) received by 98% of the volume (D 98 ), clinical target volume (CTV) D 90 , nodes D 90 , cord D 2 , and parotid D 50 and parotid mean dose were evaluated with respect to the plan used for treatment for the structure dose and for an effective planning target volume (PTV) with a 3-mm margin. Results: Simultaneous integrated boost-IMRT head-and-neck treatment plans were found to be less sensitive to random setup errors than to systematic setup errors. For random-only errors, errors exceeded 3% only when the random setup error σ exceeded 3 mm. Simulated systematic setup errors with Σ = 1.5 mm resulted in approximately 10% of plan having more than a 3% dose error, whereas a Σ = 3.0 mm resulted in half of the plans having more than a 3% dose error and 28% with a 5% dose error

Quantile Regression With Measurement Error

KAUST Repository

Wei, Ying

2009-08-27

Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.

Effect of DM Actuator Errors on the WFIRST/AFTA Coronagraph Contrast Performance

Science.gov (United States)

Sidick, Erkin; Shi, Fang

2015-01-01

The WFIRST/AFTA 2.4 m space telescope currently under study includes a stellar coronagraph for the imaging and the spectral characterization of extrasolar planets. The coronagraph employs two sequential deformable mirrors (DMs) to compensate for phase and amplitude errors in creating dark holes. DMs are critical elements in high contrast coronagraphs, requiring precision and stability measured in picometers to enable detection of Earth-like exoplanets. Working with a low-order wavefront-sensor the DM that is conjugate to a pupil can also be used to correct low-order wavefront drift during a scientific observation. However, not all actuators in a DM have the same gain. When using such a DM in low-order wavefront sensing and control subsystem, the actuator gain errors introduce high-spatial frequency errors to the DM surface and thus worsen the contrast performance of the coronagraph. We have investigated the effects of actuator gain errors and the actuator command digitization errors on the contrast performance of the coronagraph through modeling and simulations, and will present our results in this paper.

Galaxy power-spectrum responses and redshift-space super-sample effect

Science.gov (United States)

Li, Yin; Schmittfull, Marcel; Seljak, Uroš

2018-02-01

As a major source of cosmological information, galaxy clustering is susceptible to long-wavelength density and tidal fluctuations. These long modes modulate the growth and expansion rate of local structures, shifting them in both amplitude and scale. These effects are often named the growth and dilation effects, respectively. In particular the dilation shifts the baryon acoustic oscillation (BAO) peak and breaks the assumption of the Alcock-Paczynski (AP) test. This cannot be removed with reconstruction techniques because the effect originates from long modes outside the survey. In redshift space, the long modes generate a large-scale radial peculiar velocity that affects the redshift-space distortion (RSD) signal. We compute the redshift-space response functions of the galaxy power spectrum to long density and tidal modes at leading order in perturbation theory, including both the growth and dilation terms. We validate these response functions against measurements from simulated galaxy mock catalogs. As one application, long density and tidal modes beyond the scale of a survey correlate various observables leading to an excess error known as the super-sample covariance, and thus weaken their constraining power. We quantify the super-sample effect on BAO, AP, and RSD measurements, and study its impact on current and future surveys.

Common Positioning Errors in Digital Panoramic Radiographies Taken In Mashhad Dental School

Directory of Open Access Journals (Sweden)

Ali Bagherpour

2018-06-01

Full Text Available Introduction: The present study was aimed at evaluating common positioning errors on panoramic radiographs taken in the Radiology Department of Mashhad Dental School. Materials and methods: The study sample included 1,990 digital panoramic radiographs taken in the Radiology Department of Mashhad Dental School by a Planmeca Promax (Planmeca Oy, Helsinki, Finland, during a 2-year period (2010–2012. All radiographs, according to dentition and sex, were evaluated for positioning errors. Results: There were 1,927 (96.8% panoramic radiographs with one or more errors. While the number of errors in each image varied between one and five, most images had one error (48.4%. The most common error was that the tongue was not in contact with the hard palate (94.8%. "Open lips" was an error not seen in any patients. Conclusions:positioning errors are common in panoramic radiographies. The most common error observed in this study was a failure to place the tongue on the palate. This error and the other errors reported in this study can be reduced by training the technicians and spending little more time for patient positioning and more effective communication with the patients.

Checklist Usage as a Guidance on Read-Back Reducing the Potential Risk of Medication Error

Directory of Open Access Journals (Sweden)

Ida Bagus N. Maharjana

2014-06-01

Full Text Available Hospital as a last line of health services shall provide quality service and oriented on patient safety, one responsibility in preventing medication errors. Effective collaboration and communication between the profession needed to achieve patient safety. Read-back is one way of doing effective communication. Before-after study with PDCA TQM approach. The samples were on the medication chart patient medical rd rd records in the 3 week of May (before and the 3 week in July (after 2013. Treatment using the check list, asked for time 2 minutes to read-back by the doctors and nurses after the visit together. Obtained 57 samples (before and 64 samples (after. Before charging 45.54% incomplete medication chart on patient medical records that have the potential risk of medication error to 10.17% after treatment with a read back check list for 10 weeks, with 77.78% based on the achievement of the PDCA TQM approach. Checklist usage as a guidance on Read-back as an effective communication can reduce charging incompleteness drug records on medical records that have the potential risk of medication errors, 45.54% to 10.17%.

High energy hadron-induced errors in memory chips

Energy Technology Data Exchange (ETDEWEB)

Peterson, R.J. [University of Colorado, Boulder, CO (United States)

2001-09-01

We have measured probabilities for proton, neutron and pion beams from accelerators to induce temporary or soft errors in a wide range of modern 16 Mb and 64 Mb dRAM memory chips, typical of those used in aircraft electronics. Relations among the cross sections for these particles are deduced, and failure rates for aircraft avionics due to cosmic rays are evaluated. Measurement of alpha pha particle yields from pions on aluminum, as a surrogate for silicon, indicate that these reaction products are the proximate cause of the charge deposition resulting in errors. Heavy ions can cause damage to solar panels and other components in satellites above the atmosphere, by the heavy ionization trails they leave. However, at the earth's surface or at aircraft altitude it is known that cosmic rays, other than heavy ions, can cause soft errors in memory circuit components. Soft errors are those confusions between ones and zeroes that cause wrong contents to be stored in the memory, but without causing permanent damage to the circuit. As modern aircraft rely increasingly upon computerized and automated systems, these soft errors are important threats to safety. Protons, neutrons and pions resulting from high energy cosmic ray bombardment of the atmosphere pervade our environment. These particles do not induce damage directly by their ionization loss, but rather by reactions in the materials of the microcircuits. We have measured many cross sections for soft error upsets (SEU) in a broad range of commercial 16 Mb and 64 Mb dRAMs with accelerator beams. Here we define {sigma} SEU = induced errors/number of sample bits x particles/cm{sup 2}. We compare {sigma} SEU to find relations among results for these beams, and relations to reaction cross sections in order to systematize effects. We have modelled cosmic ray effects upon the components we have studied. (Author)

High energy hadron-induced errors in memory chips

International Nuclear Information System (INIS)

Peterson, R.J.

2001-01-01

We have measured probabilities for proton, neutron and pion beams from accelerators to induce temporary or soft errors in a wide range of modern 16 Mb and 64 Mb dRAM memory chips, typical of those used in aircraft electronics. Relations among the cross sections for these particles are deduced, and failure rates for aircraft avionics due to cosmic rays are evaluated. Measurement of alpha pha particle yields from pions on aluminum, as a surrogate for silicon, indicate that these reaction products are the proximate cause of the charge deposition resulting in errors. Heavy ions can cause damage to solar panels and other components in satellites above the atmosphere, by the heavy ionization trails they leave. However, at the earth's surface or at aircraft altitude it is known that cosmic rays, other than heavy ions, can cause soft errors in memory circuit components. Soft errors are those confusions between ones and zeroes that cause wrong contents to be stored in the memory, but without causing permanent damage to the circuit. As modern aircraft rely increasingly upon computerized and automated systems, these soft errors are important threats to safety. Protons, neutrons and pions resulting from high energy cosmic ray bombardment of the atmosphere pervade our environment. These particles do not induce damage directly by their ionization loss, but rather by reactions in the materials of the microcircuits. We have measured many cross sections for soft error upsets (SEU) in a broad range of commercial 16 Mb and 64 Mb dRAMs with accelerator beams. Here we define σ SEU = induced errors/number of sample bits x particles/cm 2 . We compare σ SEU to find relations among results for these beams, and relations to reaction cross sections in order to systematize effects. We have modelled cosmic ray effects upon the components we have studied. (Author)

On the effect of numerical errors in large eddy simulations of turbulent flows

International Nuclear Information System (INIS)

Kravchenko, A.G.; Moin, P.

1997-01-01

Aliased and dealiased numerical simulations of a turbulent channel flow are performed using spectral and finite difference methods. Analytical and numerical studies show that aliasing errors are more destructive for spectral and high-order finite-difference calculations than for low-order finite-difference simulations. Numerical errors have different effects for different forms of the nonlinear terms in the Navier-Stokes equations. For divergence and convective forms, spectral methods are energy-conserving only if dealiasing is performed. For skew-symmetric and rotational forms, both spectral and finite-difference methods are energy-conserving even in the presence of aliasing errors. It is shown that discrepancies between the results of dealiased spectral and standard nondialiased finite-difference methods are due to both aliasing and truncation errors with the latter being the leading source of differences. The relative importance of aliasing and truncation errors as compared to subgrid scale model terms in large eddy simulations is analyzed and discussed. For low-order finite-difference simulations, truncation errors can exceed the magnitude of the subgrid scale term. 25 refs., 17 figs., 1 tab

Gold price effect on stock market: A Markov switching vector error correction approach

Science.gov (United States)

Wai, Phoong Seuk; Ismail, Mohd Tahir; Kun, Sek Siok

2014-06-01

Gold is a popular precious metal where the demand is driven not only for practical use but also as a popular investments commodity. While stock market represents a country growth, thus gold price effect on stock market behavior as interest in the study. Markov Switching Vector Error Correction Models are applied to analysis the relationship between gold price and stock market changes since real financial data always exhibit regime switching, jumps or missing data through time. Besides, there are numerous specifications of Markov Switching Vector Error Correction Models and this paper will compare the intercept adjusted Markov Switching Vector Error Correction Model and intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model to determine the best model representation in capturing the transition of the time series. Results have shown that gold price has a positive relationship with Malaysia, Thailand and Indonesia stock market and a two regime intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model is able to provide the more significance and reliable result compare to intercept adjusted Markov Switching Vector Error Correction Models.

Effect of lethality on the extinction and on the error threshold of quasispecies.

Science.gov (United States)

Tejero, Hector; Marín, Arturo; Montero, Francisco

2010-02-21

In this paper the effect of lethality on error threshold and extinction has been studied in a population of error-prone self-replicating molecules. For given lethality and a simple fitness landscape, three dynamic regimes can be obtained: quasispecies, error catastrophe, and extinction. Using a simple model in which molecules are classified as master, lethal and non-lethal mutants, it is possible to obtain the mutation rates of the transitions between the three regimes analytically. The numerical resolution of the extended model, in which molecules are classified depending on their Hamming distance to the master sequence, confirms the results obtained in the simple model and shows how an error catastrophe regime changes when lethality is taken in account. (c) 2009 Elsevier Ltd. All rights reserved.

Stochastic and sensitivity analysis of shape error of inflatable antenna reflectors

Science.gov (United States)

San, Bingbing; Yang, Qingshan; Yin, Liwei

2017-03-01

Inflatable antennas are promising candidates to realize future satellite communications and space observations since they are lightweight, low-cost and small-packaged-volume. However, due to their high flexibility, inflatable reflectors are difficult to manufacture accurately, which may result in undesirable shape errors, and thus affect their performance negatively. In this paper, the stochastic characteristics of shape errors induced during manufacturing process are investigated using Latin hypercube sampling coupled with manufacture simulations. Four main random error sources are involved, including errors in membrane thickness, errors in elastic modulus of membrane, boundary deviations and pressure variations. Using regression and correlation analysis, a global sensitivity study is conducted to rank the importance of these error sources. This global sensitivity analysis is novel in that it can take into account the random variation and the interaction between error sources. Analyses are parametrically carried out with various focal-length-to-diameter ratios (F/D) and aperture sizes (D) of reflectors to investigate their effects on significance ranking of error sources. The research reveals that RMS (Root Mean Square) of shape error is a random quantity with an exponent probability distribution and features great dispersion; with the increase of F/D and D, both mean value and standard deviation of shape errors are increased; in the proposed range, the significance ranking of error sources is independent of F/D and D; boundary deviation imposes the greatest effect with a much higher weight than the others; pressure variation ranks the second; error in thickness and elastic modulus of membrane ranks the last with very close sensitivities to pressure variation. Finally, suggestions are given for the control of the shape accuracy of reflectors and allowable values of error sources are proposed from the perspective of reliability.

Non-uniform sampling and wide range angular spectrum method

International Nuclear Information System (INIS)

Kim, Yong-Hae; Byun, Chun-Won; Oh, Himchan; Lee, JaeWon; Pi, Jae-Eun; Heon Kim, Gi; Lee, Myung-Lae; Ryu, Hojun; Chu, Hye-Yong; Hwang, Chi-Sun

2014-01-01

A novel method is proposed for simulating free space field propagation from a source plane to a destination plane that is applicable for both small and large propagation distances. The angular spectrum method (ASM) was widely used for simulating near field propagation, but it caused a numerical error when the propagation distance was large because of aliasing due to under sampling. Band limited ASM satisfied the Nyquist condition on sampling by limiting a bandwidth of a propagation field to avoid an aliasing error so that it could extend the applicable propagation distance of the ASM. However, the band limited ASM also made an error due to the decrease of an effective sampling number in a Fourier space when the propagation distance was large. In the proposed wide range ASM, we use a non-uniform sampling in a Fourier space to keep a constant effective sampling number even though the propagation distance is large. As a result, the wide range ASM can produce simulation results with high accuracy for both far and near field propagation. For non-paraxial wave propagation, we applied the wide range ASM to a shifted destination plane as well. (paper)

Error-related brain activity and error awareness in an error classification paradigm.

Science.gov (United States)

Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E

2016-10-01

Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error.

Science.gov (United States)

Faber, Felix A; Hutchison, Luke; Huang, Bing; Gilmer, Justin; Schoenholz, Samuel S; Dahl, George E; Vinyals, Oriol; Kearnes, Steven; Riley, Patrick F; von Lilienfeld, O Anatole

2017-11-14

We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of 13 electronic ground-state properties of organic molecules. The performance of each regressor/representation/property combination is assessed using learning curves which report out-of-sample errors as a function of training set size with up to ∼118k distinct molecules. Molecular structures and properties at the hybrid density functional theory (DFT) level of theory come from the QM9 database [ Ramakrishnan et al. Sci. Data 2014 , 1 , 140022 ] and include enthalpies and free energies of atomization, HOMO/LUMO energies and gap, dipole moment, polarizability, zero point vibrational energy, heat capacity, and the highest fundamental vibrational frequency. Various molecular representations have been studied (Coulomb matrix, bag of bonds, BAML and ECFP4, molecular graphs (MG)), as well as newly developed distribution based variants including histograms of distances (HD), angles (HDA/MARAD), and dihedrals (HDAD). Regressors include linear models (Bayesian ridge regression (BR) and linear regression with elastic net regularization (EN)), random forest (RF), kernel ridge regression (KRR), and two types of neural networks, graph convolutions (GC) and gated graph networks (GG). Out-of sample errors are strongly dependent on the choice of representation and regressor and molecular property. Electronic properties are typically best accounted for by MG and GC, while energetic properties are better described by HDAD and KRR. The specific combinations with the lowest out-of-sample errors in the ∼118k training set size limit are (free) energies and enthalpies of atomization (HDAD/KRR), HOMO/LUMO eigenvalue and gap (MG/GC), dipole moment (MG/GC), static polarizability (MG/GG), zero point vibrational energy (HDAD/KRR), heat capacity at room temperature (HDAD/KRR), and highest fundamental vibrational frequency (BAML/RF). We present numerical

A study of total measurement error in tomographic gamma scanning to assay nuclear material with emphasis on a bias issue for low-activity samples

International Nuclear Information System (INIS)

Burr, T.L.; Mercer, D.J.; Prettyman, T.H.

1998-01-01

Field experience with the tomographic gamma scanner to assay nuclear material suggests that the analysis techniques can significantly impact the assay uncertainty. For example, currently implemented image reconstruction methods exhibit a positive bias for low-activity samples. Preliminary studies indicate that bias reduction could be achieved at the expense of increased random error variance. In this paper, the authors examine three possible bias sources: (1) measurement error in the estimated transmission matrix, (2) the positivity constraint on the estimated mass of nuclear material, and (3) improper treatment of the measurement error structure. The authors present results from many small-scale simulation studies to examine this bias/variance tradeoff for a few image reconstruction methods in the presence of the three possible bias sources

A study of the effect of measurement error in predictor variables in nondestructive assay

International Nuclear Information System (INIS)

Burr, Tom L.; Knepper, Paula L.

2000-01-01

It is not widely known that ordinary least squares estimates exhibit bias if there are errors in the predictor variables. For example, enrichment measurements are often fit to two predictors: Poisson-distributed count rates in the region of interest and in the background. Both count rates have at least random variation due to counting statistics. Therefore, the parameter estimates will be biased. In this case, the effect of bias is a minor issue because there is almost no interest in the parameters themselves. Instead, the parameters will be used to convert count rates into estimated enrichment. In other cases, this bias source is potentially more important. For example, in tomographic gamma scanning, there is an emission stage which depends on predictors (the 'system matrix') that are estimated with error during the transmission stage. In this paper, we provide background information for the impact and treatment of errors in predictors, present results of candidate methods of compensating for the effect, review some of the nondestructive assay situations where errors in predictors occurs, and provide guidance for when errors in predictors should be considered in nondestructive assay

[Practical aspects regarding sample size in clinical research].

Science.gov (United States)

Vega Ramos, B; Peraza Yanes, O; Herrera Correa, G; Saldívar Toraya, S

1996-01-01

The knowledge of the right sample size let us to be sure if the published results in medical papers had a suitable design and a proper conclusion according to the statistics analysis. To estimate the sample size we must consider the type I error, type II error, variance, the size of the effect, significance and power of the test. To decide what kind of mathematics formula will be used, we must define what kind of study we have, it means if its a prevalence study, a means values one or a comparative one. In this paper we explain some basic topics of statistics and we describe four simple samples of estimation of sample size.

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

Directory of Open Access Journals (Sweden)

Laura Marchal-Crespo

2017-09-01

Full Text Available Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL, i.e., precuneus, and temporal cortex. These neuroimaging findings

45 CFR 98.100 - Error Rate Report.

Science.gov (United States)

2010-10-01

... Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ADMINISTRATION CHILD CARE AND DEVELOPMENT FUND... the total dollar amount of payments made in the sample); the average amount of improper payment; and... not received. (e) Costs of Preparing the Error Rate Report—Provided the error rate calculations and...

Error analysis of stochastic gradient descent ranking.

Science.gov (United States)

Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

2013-06-01

Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

High cortisol awakening response is associated with impaired error monitoring and decreased post-error adjustment.

Science.gov (United States)

Zhang, Liang; Duan, Hongxia; Qin, Shaozheng; Yuan, Yiran; Buchanan, Tony W; Zhang, Kan; Wu, Jianhui

2015-01-01

The cortisol awakening response (CAR), a rapid increase in cortisol levels following morning awakening, is an important aspect of hypothalamic-pituitary-adrenocortical axis activity. Alterations in the CAR have been linked to a variety of mental disorders and cognitive function. However, little is known regarding the relationship between the CAR and error processing, a phenomenon that is vital for cognitive control and behavioral adaptation. Using high-temporal resolution measures of event-related potentials (ERPs) combined with behavioral assessment of error processing, we investigated whether and how the CAR is associated with two key components of error processing: error detection and subsequent behavioral adjustment. Sixty university students performed a Go/No-go task while their ERPs were recorded. Saliva samples were collected at 0, 15, 30 and 60 min after awakening on the two consecutive days following ERP data collection. The results showed that a higher CAR was associated with slowed latency of the error-related negativity (ERN) and a higher post-error miss rate. The CAR was not associated with other behavioral measures such as the false alarm rate and the post-correct miss rate. These findings suggest that high CAR is a biological factor linked to impairments of multiple steps of error processing in healthy populations, specifically, the automatic detection of error and post-error behavioral adjustment. A common underlying neural mechanism of physiological and cognitive control may be crucial for engaging in both CAR and error processing.

Theory of sampling: four critical success factors before analysis.

Science.gov (United States)

Wagner, Claas; Esbensen, Kim H

2015-01-01

Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data, stemming from representative samples. The Theory of Sampling (TOS) is the only comprehensive theoretical framework that fully defines all requirements to ensure sampling correctness and representativity, and to provide the guiding principles for sampling in practice. TOS also defines the concept of material heterogeneity and its impact on the sampling process, including the effects from all potential sampling errors. TOS's primary task is to eliminate bias-generating errors and to minimize sampling variability. Quantitative measures are provided to characterize material heterogeneity, on which an optimal sampling strategy should be based. Four critical success factors preceding analysis to ensure a representative sampling process are presented here.

A new method for weakening the combined effect of residual errors on multibeam bathymetric data

Science.gov (United States)

Zhao, Jianhu; Yan, Jun; Zhang, Hongmei; Zhang, Yuqing; Wang, Aixue

2014-12-01

Multibeam bathymetric system (MBS) has been widely applied in the marine surveying for providing high-resolution seabed topography. However, some factors degrade the precision of bathymetry, including the sound velocity, the vessel attitude, the misalignment angle of the transducer and so on. Although these factors have been corrected strictly in bathymetric data processing, the final bathymetric result is still affected by their residual errors. In deep water, the result usually cannot meet the requirements of high-precision seabed topography. The combined effect of these residual errors is systematic, and it's difficult to separate and weaken the effect using traditional single-error correction methods. Therefore, the paper puts forward a new method for weakening the effect of residual errors based on the frequency-spectrum characteristics of seabed topography and multibeam bathymetric data. Four steps, namely the separation of the low-frequency and the high-frequency part of bathymetric data, the reconstruction of the trend of actual seabed topography, the merging of the actual trend and the extracted microtopography, and the accuracy evaluation, are involved in the method. Experiment results prove that the proposed method could weaken the combined effect of residual errors on multibeam bathymetric data and efficiently improve the accuracy of the final post-processing results. We suggest that the method should be widely applied to MBS data processing in deep water.

Repeated speech errors: evidence for learning.

Science.gov (United States)

Humphreys, Karin R; Menzies, Heather; Lake, Johanna K

2010-11-01

Three experiments elicited phonological speech errors using the SLIP procedure to investigate whether there is a tendency for speech errors on specific words to reoccur, and whether this effect can be attributed to implicit learning of an incorrect mapping from lemma to phonology for that word. In Experiment 1, when speakers made a phonological speech error in the study phase of the experiment (e.g. saying "beg pet" in place of "peg bet") they were over four times as likely to make an error on that same item several minutes later at test. A pseudo-error condition demonstrated that the effect is not simply due to a propensity for speakers to repeat phonological forms, regardless of whether or not they have been made in error. That is, saying "beg pet" correctly at study did not induce speakers to say "beg pet" in error instead of "peg bet" at test. Instead, the effect appeared to be due to learning of the error pathway. Experiment 2 replicated this finding, but also showed that after 48 h, errors made at study were no longer more likely to reoccur. As well as providing constraints on the longevity of the effect, this provides strong evidence that the error reoccurrences observed are not due to item-specific difficulty that leads individual speakers to make habitual mistakes on certain items. Experiment 3 showed that the diminishment of the effect 48 h later is not due to specific extra practice at the task. We discuss how these results fit in with a larger view of language as a dynamic system that is constantly adapting in response to experience. Copyright © 2010 Elsevier B.V. All rights reserved.

Population size estimation in Yellowstone wolves with error-prone noninvasive microsatellite genotypes.

Science.gov (United States)

Creel, Scott; Spong, Goran; Sands, Jennifer L; Rotella, Jay; Zeigle, Janet; Joe, Lawrence; Murphy, Kerry M; Smith, Douglas

2003-07-01

Determining population sizes can be difficult, but is essential for conservation. By counting distinct microsatellite genotypes, DNA from noninvasive samples (hair, faeces) allows estimation of population size. Problems arise because genotypes from noninvasive samples are error-prone, but genotyping errors can be reduced by multiple polymerase chain reaction (PCR). For faecal genotypes from wolves in Yellowstone National Park, error rates varied substantially among samples, often above the 'worst-case threshold' suggested by simulation. Consequently, a substantial proportion of multilocus genotypes held one or more errors, despite multiple PCR. These genotyping errors created several genotypes per individual and caused overestimation (up to 5.5-fold) of population size. We propose a 'matching approach' to eliminate this overestimation bias.

On systematic and statistic errors in radionuclide mass activity estimation procedure

International Nuclear Information System (INIS)

Smelcerovic, M.; Djuric, G.; Popovic, D.

1989-01-01

One of the most important requirements during nuclear accidents is the fast estimation of the mass activity of the radionuclides that suddenly and without control reach the environment. The paper points to systematic errors in the procedures of sampling, sample preparation and measurement itself, that in high degree contribute to total mass activity evaluation error. Statistic errors in gamma spectrometry as well as in total mass alpha and beta activity evaluation are also discussed. Beside, some of the possible sources of errors in the partial mass activity evaluation for some of the radionuclides are presented. The contribution of the errors in the total mass activity evaluation error is estimated and procedures that could possibly reduce it are discussed (author)

Impact of Educational Activities in Reducing Pre-Analytical Laboratory Errors: A quality initiative.

Science.gov (United States)

Al-Ghaithi, Hamed; Pathare, Anil; Al-Mamari, Sahimah; Villacrucis, Rodrigo; Fawaz, Naglaa; Alkindi, Salam

2017-08-01

Pre-analytic errors during diagnostic laboratory investigations can lead to increased patient morbidity and mortality. This study aimed to ascertain the effect of educational nursing activities on the incidence of pre-analytical errors resulting in non-conforming blood samples. This study was conducted between January 2008 and December 2015. All specimens received at the Haematology Laboratory of the Sultan Qaboos University Hospital, Muscat, Oman, during this period were prospectively collected and analysed. Similar data from 2007 were collected retrospectively and used as a baseline for comparison. Non-conforming samples were defined as either clotted samples, haemolysed samples, use of the wrong anticoagulant, insufficient quantities of blood collected, incorrect/lack of labelling on a sample or lack of delivery of a sample in spite of a sample request. From 2008 onwards, multiple educational training activities directed at the hospital nursing staff and nursing students primarily responsible for blood collection were implemented on a regular basis. After initiating corrective measures in 2008, a progressive reduction in the percentage of non-conforming samples was observed from 2009 onwards. Despite a 127.84% increase in the total number of specimens received, there was a significant reduction in non-conforming samples from 0.29% in 2007 to 0.07% in 2015, resulting in an improvement of 75.86% ( P educational activities directed primarily towards hospital nursing staff had a positive impact on the quality of laboratory specimens by significantly reducing pre-analytical errors.

Analysis of Wind Speed Forecasting Error Effects on Automatic Generation Control Performance

Directory of Open Access Journals (Sweden)

H. Rajabi Mashhadi

2014-09-01

Full Text Available The main goal of this paper is to study statistical indices and evaluate AGC indices in power system which has large penetration of the WTGs. Increasing penetration of wind turbine generations, needs to study more about impacts of it on power system frequency control. Frequency control is changed with unbalancing real-time system generation and load . Also wind turbine generations have more fluctuations and make system more unbalance. Then AGC loop helps to adjust system frequency and the scheduled tie-line powers. The quality of AGC loop is measured by some indices. A good index is a proper measure shows the AGC performance just as the power system operates. One of well-known measures in literature which was introduced by NERC is Control Performance Standards(CPS. Previously it is claimed that a key factor in CPS index is related to standard deviation of generation error, installed power and frequency response. This paper focuses on impact of a several hours-ahead wind speed forecast error on this factor. Furthermore evaluation of conventional control performances in the power systems with large-scale wind turbine penetration is studied. Effects of wind speed standard deviation and also degree of wind farm penetration are analyzed and importance of mentioned factor are criticized. In addition, influence of mean wind speed forecast error on this factor is investigated. The study system is a two area system which there is significant wind farm in one of those. The results show that mean wind speed forecast error has considerable effect on AGC performance while the mentioned key factor is insensitive to this mean error.

An Empirical State Error Covariance Matrix for Batch State Estimation

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Frisbee, Joseph H., Jr.

2011-01-01

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the

Reducing systematic errors in measurements made by a SQUID magnetometer

International Nuclear Information System (INIS)

Kiss, L.F.; Kaptás, D.; Balogh, J.

2014-01-01

A simple method is described which reduces those systematic errors of a superconducting quantum interference device (SQUID) magnetometer that arise from possible radial displacements of the sample in the second-order gradiometer superconducting pickup coil. By rotating the sample rod (and hence the sample) around its axis into a position where the best fit is obtained to the output voltage of the SQUID as the sample is moved through the pickup coil, the accuracy of measuring magnetic moments can be increased significantly. In the cases of an examined Co 1.9 Fe 1.1 Si Heusler alloy, pure iron and nickel samples, the accuracy could be increased over the value given in the specification of the device. The suggested method is only meaningful if the measurement uncertainty is dominated by systematic errors – radial displacement in particular – and not by instrumental or environmental noise. - Highlights: • A simple method is described which reduces systematic errors of a SQUID. • The errors arise from a radial displacement of the sample in the gradiometer coil. • The procedure is to rotate the sample rod (with the sample) around its axis. • The best fit to the SQUID voltage has to be attained moving the sample through the coil. • The accuracy of measuring magnetic moment can be increased significantly

A theory of human error

Science.gov (United States)

Mcruer, D. T.; Clement, W. F.; Allen, R. W.

1981-01-01

Human errors tend to be treated in terms of clinical and anecdotal descriptions, from which remedial measures are difficult to derive. Correction of the sources of human error requires an attempt to reconstruct underlying and contributing causes of error from the circumstantial causes cited in official investigative reports. A comprehensive analytical theory of the cause-effect relationships governing propagation of human error is indispensable to a reconstruction of the underlying and contributing causes. A validated analytical theory of the input-output behavior of human operators involving manual control, communication, supervisory, and monitoring tasks which are relevant to aviation, maritime, automotive, and process control operations is highlighted. This theory of behavior, both appropriate and inappropriate, provides an insightful basis for investigating, classifying, and quantifying the needed cause-effect relationships governing propagation of human error.

Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling: A case study in environmental remote sensing

Science.gov (United States)

Gao, Jing; Burt, James E.

2017-12-01

This study investigates the usefulness of a per-pixel bias-variance error decomposition (BVD) for understanding and improving spatially-explicit data-driven models of continuous variables in environmental remote sensing (ERS). BVD is a model evaluation method originated from machine learning and have not been examined for ERS applications. Demonstrated with a showcase regression tree model mapping land imperviousness (0-100%) using Landsat images, our results showed that BVD can reveal sources of estimation errors, map how these sources vary across space, reveal the effects of various model characteristics on estimation accuracy, and enable in-depth comparison of different error metrics. Specifically, BVD bias maps can help analysts identify and delineate model spatial non-stationarity; BVD variance maps can indicate potential effects of ensemble methods (e.g. bagging), and inform efficient training sample allocation - training samples should capture the full complexity of the modeled process, and more samples should be allocated to regions with more complex underlying processes rather than regions covering larger areas. Through examining the relationships between model characteristics and their effects on estimation accuracy revealed by BVD for both absolute and squared errors (i.e. error is the absolute or the squared value of the difference between observation and estimate), we found that the two error metrics embody different diagnostic emphases, can lead to different conclusions about the same model, and may suggest different solutions for performance improvement. We emphasize BVD's strength in revealing the connection between model characteristics and estimation accuracy, as understanding this relationship empowers analysts to effectively steer performance through model adjustments.

Radiation effects and soft errors in integrated circuits and electronic devices

CERN Document Server

Fleetwood, D M

2004-01-01

This book provides a detailed treatment of radiation effects in electronic devices, including effects at the material, device, and circuit levels. The emphasis is on transient effects caused by single ionizing particles (single-event effects and soft errors) and effects produced by the cumulative energy deposited by the radiation (total ionizing dose effects). Bipolar (Si and SiGe), metal-oxide-semiconductor (MOS), and compound semiconductor technologies are discussed. In addition to considering the specific issues associated with high-performance devices and technologies, the book includes th

Total elimination of sampling errors in polarization imagery obtained with integrated microgrid polarimeters.

Science.gov (United States)

Tyo, J Scott; LaCasse, Charles F; Ratliff, Bradley M

2009-10-15

Microgrid polarimeters operate by integrating a focal plane array with an array of micropolarizers. The Stokes parameters are estimated by comparing polarization measurements from pixels in a neighborhood around the point of interest. The main drawback is that the measurements used to estimate the Stokes vector are made at different locations, leading to a false polarization signature owing to instantaneous field-of-view (IFOV) errors. We demonstrate for the first time, to our knowledge, that spatially band limited polarization images can be ideally reconstructed with no IFOV error by using a linear system framework.

Random and systematic sampling error when hooking fish to monitor skin fluke (Benedenia seriolae) and gill fluke (Zeuxapta seriolae) burden in Australian farmed yellowtail kingfish (Seriola lalandi).

Science.gov (United States)

Fensham, J R; Bubner, E; D'Antignana, T; Landos, M; Caraguel, C G B

2018-05-01

The Australian farmed yellowtail kingfish (Seriola lalandi, YTK) industry monitor skin fluke (Benedenia seriolae) and gill fluke (Zeuxapta seriolae) burden by pooling the fluke count of 10 hooked YTK. The random and systematic error of this sampling strategy was evaluated to assess potential impact on treatment decisions. Fluke abundance (fluke count per fish) in a study cage (estimated 30,502 fish) was assessed five times using the current sampling protocol and its repeatability was estimated the repeatability coefficient (CR) and the coefficient of variation (CV). Individual body weight, fork length, fluke abundance, prevalence, intensity (fluke count per infested fish) and density (fluke count per Kg of fish) were compared between 100 hooked and 100 seined YTK (assumed representative of the entire population) to estimate potential selection bias. Depending on the fluke species and age category, CR (expected difference in parasite count between 2 sampling iterations) ranged from 0.78 to 114 flukes per fish. Capturing YTK by hooking increased the selection of fish of a weight and length in the lowest 5th percentile of the cage (RR = 5.75, 95% CI: 2.06-16.03, P-value = 0.0001). These lower end YTK had on average an extra 31 juveniles and 6 adults Z. seriolae per Kg of fish and an extra 3 juvenile and 0.4 adult B. seriolae per Kg of fish, compared to the rest of the cage population (P-value sampling towards the smallest and most heavily infested fish in the population, resulting in poor repeatability (more variability amongst sampled fish) and an overestimation of parasite burden in the population. In this particular commercial situation these finding supported that health management program, where the finding of an underestimation of parasite burden could provide a production impact on the study population. In instances where fish populations and parasite burdens are more homogenous, sampling error may be less severe. Sampling error when capturing fish

Statistical learning from nonrecurrent experience with discrete input variables and recursive-error-minimization equations

Science.gov (United States)

Carter, Jeffrey R.; Simon, Wayne E.

1990-08-01

Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and

The perils of straying from protocol: sampling bias and interviewer effects.

Directory of Open Access Journals (Sweden)

Carrie J Ngongo

Full Text Available Fidelity to research protocol is critical. In a contingent valuation study in an informal urban settlement in Nairobi, Kenya, participants responded differently to the three trained interviewers. Interviewer effects were present during the survey pilot, then magnified at the start of the main survey after a seemingly slight adaptation of the survey sampling protocol allowed interviewers to speak with the "closest neighbor" in the event that no one was home at a selected household. This slight degree of interviewer choice led to inferred sampling bias. Multinomial logistic regression and post-estimation tests revealed that the three interviewers' samples differed significantly from one another according to six demographic characteristics. The two female interviewers were 2.8 and 7.7 times less likely to talk with respondents of low socio-economic status than the male interviewer. Systematic error renders it impossible to determine which of the survey responses might be "correct." This experience demonstrates why researchers must take care to strictly follow sampling protocols, consistently train interviewers, and monitor responses by interview to ensure similarity between interviewers' groups and produce unbiased estimates of the parameters of interest.

Approximation errors during variance propagation

International Nuclear Information System (INIS)

Dinsmore, Stephen

1986-01-01

Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given

Classification based upon gene expression data: bias and precision of error rates.

Science.gov (United States)

Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

2007-06-01

Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

How Much Confidence Can We Have in EU-SILC? Complex Sample Designs and the Standard Error of the Europe 2020 Poverty Indicators

Science.gov (United States)

Goedeme, Tim

2013-01-01

If estimates are based on samples, they should be accompanied by appropriate standard errors and confidence intervals. This is true for scientific research in general, and is even more important if estimates are used to inform and evaluate policy measures such as those aimed at attaining the Europe 2020 poverty reduction target. In this article I…

Errors in practical measurement in surveying, engineering, and technology

International Nuclear Information System (INIS)

Barry, B.A.; Morris, M.D.

1991-01-01

This book discusses statistical measurement, error theory, and statistical error analysis. The topics of the book include an introduction to measurement, measurement errors, the reliability of measurements, probability theory of errors, measures of reliability, reliability of repeated measurements, propagation of errors in computing, errors and weights, practical application of the theory of errors in measurement, two-dimensional errors and includes a bibliography. Appendices are included which address significant figures in measurement, basic concepts of probability and the normal probability curve, writing a sample specification for a procedure, classification, standards of accuracy, and general specifications of geodetic control surveys, the geoid, the frequency distribution curve and the computer and calculator solution of problems

Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation

Science.gov (United States)

Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.

2018-01-01

Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.

Modeling coherent errors in quantum error correction

Science.gov (United States)

Greenbaum, Daniel; Dutton, Zachary

2018-01-01

Analysis of quantum error correcting codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. Here we examine the accuracy of the Pauli approximation for noise containing coherent errors (characterized by a rotation angle ɛ) under the repetition code. We derive an analytic expression for the logical error channel as a function of arbitrary code distance d and concatenation level n, in the small error limit. We find that coherent physical errors result in logical errors that are partially coherent and therefore non-Pauli. However, the coherent part of the logical error is negligible at fewer than {ε }-({dn-1)} error correction cycles when the decoder is optimized for independent Pauli errors, thus providing a regime of validity for the Pauli approximation. Above this number of correction cycles, the persistent coherent logical error will cause logical failure more quickly than the Pauli model would predict, and this may need to be combated with coherent suppression methods at the physical level or larger codes.

Big Data, Small Sample.

Science.gov (United States)

Gerlovina, Inna; van der Laan, Mark J; Hubbard, Alan

2017-05-20

Multiple comparisons and small sample size, common characteristics of many types of "Big Data" including those that are produced by genomic studies, present specific challenges that affect reliability of inference. Use of multiple testing procedures necessitates calculation of very small tail probabilities of a test statistic distribution. Results based on large deviation theory provide a formal condition that is necessary to guarantee error rate control given practical sample sizes, linking the number of tests and the sample size; this condition, however, is rarely satisfied. Using methods that are based on Edgeworth expansions (relying especially on the work of Peter Hall), we explore the impact of departures of sampling distributions from typical assumptions on actual error rates. Our investigation illustrates how far the actual error rates can be from the declared nominal levels, suggesting potentially wide-spread problems with error rate control, specifically excessive false positives. This is an important factor that contributes to "reproducibility crisis". We also review some other commonly used methods (such as permutation and methods based on finite sampling inequalities) in their application to multiple testing/small sample data. We point out that Edgeworth expansions, providing higher order approximations to the sampling distribution, offer a promising direction for data analysis that could improve reliability of studies relying on large numbers of comparisons with modest sample sizes.

Errors in self-reports of health services use: impact on alzheimer disease clinical trial designs.

Science.gov (United States)

Callahan, Christopher M; Tu, Wanzhu; Stump, Timothy E; Clark, Daniel O; Unroe, Kathleen T; Hendrie, Hugh C

2015-01-01

Most Alzheimer disease clinical trials that compare the use of health services rely on reports of caregivers. The goal of this study was to assess the accuracy of self-reports among older adults with Alzheimer disease and their caregiver proxy respondents. This issue is particularly relevant to Alzheimer disease clinical trials because inaccuracy can lead both to loss of power and increased bias in study outcomes. We compared respondent accuracy in reporting any use and in reporting the frequency of use with actual utilization data as documented in a comprehensive database. We next simulated the impact of underreporting and overreporting on sample size estimates and treatment effect bias for clinical trials comparing utilization between experimental groups. Respondents self-reports have a poor level of accuracy with κ-values often below 0.5. Respondents tend to underreport use even for rare events such as hospitalizations and nursing home stays. In analyses simulating underreporting and overreporting of varying magnitude, we found that errors in self-reports can increase the required sample size by 15% to 30%. In addition, bias in the reported treatment effect ranged from 3% to 18% due to both underreporting and overreporting errors. Use of self-report data in clinical trials of Alzheimer disease treatments may inflate sample size needs. Even when adequate power is achieved by increasing sample size, reporting errors can result in a biased estimate of the true effect size of the intervention.

Error management process for power stations

International Nuclear Information System (INIS)

Hirotsu, Yuko; Takeda, Daisuke; Fujimoto, Junzo; Nagasaka, Akihiko

2016-01-01

The purpose of this study is to establish 'error management process for power stations' for systematizing activities for human error prevention and for festering continuous improvement of these activities. The following are proposed by deriving concepts concerning error management process from existing knowledge and realizing them through application and evaluation of their effectiveness at a power station: an entire picture of error management process that facilitate four functions requisite for maraging human error prevention effectively (1. systematizing human error prevention tools, 2. identifying problems based on incident reports and taking corrective actions, 3. identifying good practices and potential problems for taking proactive measures, 4. prioritizeng human error prevention tools based on identified problems); detail steps for each activity (i.e. developing an annual plan for human error prevention, reporting and analyzing incidents and near misses) based on a model of human error causation; procedures and example of items for identifying gaps between current and desired levels of executions and outputs of each activity; stages for introducing and establishing the above proposed error management process into a power station. By giving shape to above proposals at a power station, systematization and continuous improvement of activities for human error prevention in line with the actual situation of the power station can be expected. (author)

On the effects of systematic errors in analysis of nuclear scattering data

International Nuclear Information System (INIS)

Bennett, M.T.; Steward, C.; Amos, K.; Allen, L.J.

1995-01-01

The effects of systematic errors on elastic scattering differential cross-section data upon the assessment of quality fits to that data have been studied. Three cases are studied, namely the differential cross-section data sets from elastic scattering of 200 MeV protons from 12 C, of 350 MeV 16 O- 16 O scattering and of 288.6 MeV 12 C- 12 C scattering. First, to estimate the probability of any unknown systematic errors, select sets of data have been processed using the method of generalized cross validation; a method based upon the premise that any data set should satisfy an optimal smoothness criterion. In another case, the S function that provided a statistically significant fit to data, upon allowance for angle variation, became overdetermined. A far simpler S function form could then be found to describe the scattering process. The S functions so obtained have been used in a fixed energy inverse scattering study to specify effective, local, Schroedinger potentials for the collisions. An error analysis has been performed on the results to specify confidence levels for those interactions. 19 refs., 6 tabs., 15 figs

Passive quantum error correction of linear optics networks through error averaging

Science.gov (United States)

Marshman, Ryan J.; Lund, Austin P.; Rohde, Peter P.; Ralph, Timothy C.

2018-02-01

We propose and investigate a method of error detection and noise correction for bosonic linear networks using a method of unitary averaging. The proposed error averaging does not rely on ancillary photons or control and feedforward correction circuits, remaining entirely passive in its operation. We construct a general mathematical framework for this technique and then give a series of proof of principle examples including numerical analysis. Two methods for the construction of averaging are then compared to determine the most effective manner of implementation and probe the related error thresholds. Finally we discuss some of the potential uses of this scheme.

Effects of errors and gaps in spatial data sets on assessment of conservation progress.

Science.gov (United States)

Visconti, P; Di Marco, M; Álvarez-Romero, J G; Januchowski-Hartley, S R; Pressey, R L; Weeks, R; Rondinini, C

2013-10-01

Data on the location and extent of protected areas, ecosystems, and species' distributions are essential for determining gaps in biodiversity protection and identifying future conservation priorities. However, these data sets always come with errors in the maps and associated metadata. Errors are often overlooked in conservation studies, despite their potential negative effects on the reported extent of protection of species and ecosystems. We used 3 case studies to illustrate the implications of 3 sources of errors in reporting progress toward conservation objectives: protected areas with unknown boundaries that are replaced by buffered centroids, propagation of multiple errors in spatial data, and incomplete protected-area data sets. As of 2010, the frequency of protected areas with unknown boundaries in the World Database on Protected Areas (WDPA) caused the estimated extent of protection of 37.1% of the terrestrial Neotropical mammals to be overestimated by an average 402.8% and of 62.6% of species to be underestimated by an average 10.9%. Estimated level of protection of the world's coral reefs was 25% higher when using recent finer-resolution data on coral reefs as opposed to globally available coarse-resolution data. Accounting for additional data sets not yet incorporated into WDPA contributed up to 6.7% of additional protection to marine ecosystems in the Philippines. We suggest ways for data providers to reduce the errors in spatial and ancillary data and ways for data users to mitigate the effects of these errors on biodiversity assessments. © 2013 Society for Conservation Biology.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

Science.gov (United States)

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

Effect of Antenna Pointing Errors on SAR Imaging Considering the Change of the Point Target Location

Science.gov (United States)

Zhang, Xin; Liu, Shijie; Yu, Haifeng; Tong, Xiaohua; Huang, Guoman

2018-04-01

Towards spaceborne spotlight SAR, the antenna is regulated by the SAR system with specific regularity, so the shaking of the internal mechanism is inevitable. Moreover, external environment also has an effect on the stability of SAR platform. Both of them will cause the jitter of the SAR platform attitude. The platform attitude instability will introduce antenna pointing error on both the azimuth and range directions, and influence the acquisition of SAR original data and ultimate imaging quality. In this paper, the relations between the antenna pointing errors and the three-axis attitude errors are deduced, then the relations between spaceborne spotlight SAR imaging of the point target and antenna pointing errors are analysed based on the paired echo theory, meanwhile, the change of the azimuth antenna gain is considered as the spotlight SAR platform moves ahead. The simulation experiments manifest the effects on spotlight SAR imaging caused by antenna pointing errors are related to the target location, that is, the pointing errors of the antenna beam will severely influence the area far away from the scene centre of azimuth direction in the illuminated scene.

The effect on dose accumulation accuracy of inverse-consistency and transitivity error reduced deformation maps

International Nuclear Information System (INIS)

Hardcastle, Nicholas; Bender, Edward T.; Tomé, Wolfgang A.

2014-01-01

It has previously been shown that deformable image registrations (DIRs) often result in deformation maps that are neither inverse-consistent nor transitive, and that the dose accumulation based on these deformation maps can be inconsistent if different image pathways are used for dose accumulation. A method presented to reduce inverse consistency and transitivity errors has been shown to result in more consistent dose accumulation, regardless of the image pathway selected for dose accumulation. The present study investigates the effect on the dose accumulation accuracy of deformation maps processed to reduce inverse consistency and transitivity errors. A set of lung 4DCT phases were analysed, consisting of four images on which a dose grid was created. Dose to 75 corresponding anatomical locations was manually tracked. Dose accumulation was performed between all image sets with Demons derived deformation maps as well as deformation maps processed to reduce inverse consistency and transitivity errors. The ground truth accumulated dose was then compared with the accumulated dose derived from DIR. Two dose accumulation image pathways were considered. The post-processing method to reduce inverse consistency and transitivity errors had minimal effect on the dose accumulation accuracy. There was a statistically significant improvement in dose accumulation accuracy for one pathway, but for the other pathway there was no statistically significant difference. A post-processing technique to reduce inverse consistency and transitivity errors has a positive, yet minimal effect on the dose accumulation accuracy. Thus the post-processing technique improves consistency of dose accumulation with minimal effect on dose accumulation accuracy.

Motoneuron axon pathfinding errors in zebrafish: Differential effects related to concentration and timing of nicotine exposure

International Nuclear Information System (INIS)

Menelaou, Evdokia; Paul, Latoya T.; Perera, Surangi N.; Svoboda, Kurt R.

2015-01-01

Nicotine exposure during embryonic stages of development can affect many neurodevelopmental processes. In the developing zebrafish, exposure to nicotine was reported to cause axonal pathfinding errors in the later born secondary motoneurons (SMNs). These alterations in SMN axon morphology coincided with muscle degeneration at high nicotine concentrations (15–30 μM). Previous work showed that the paralytic mutant zebrafish known as sofa potato exhibited nicotine-induced effects onto SMN axons at these high concentrations but in the absence of any muscle deficits, indicating that pathfinding errors could occur independent of muscle effects. In this study, we used varying concentrations of nicotine at different developmental windows of exposure to specifically isolate its effects onto subpopulations of motoneuron axons. We found that nicotine exposure can affect SMN axon morphology in a dose-dependent manner. At low concentrations of nicotine, SMN axons exhibited pathfinding errors, in the absence of any nicotine-induced muscle abnormalities. Moreover, the nicotine exposure paradigms used affected the 3 subpopulations of SMN axons differently, but the dorsal projecting SMN axons were primarily affected. We then identified morphologically distinct pathfinding errors that best described the nicotine-induced effects on dorsal projecting SMN axons. To test whether SMN pathfinding was potentially influenced by alterations in the early born primary motoneuron (PMN), we performed dual labeling studies, where both PMN and SMN axons were simultaneously labeled with antibodies. We show that only a subset of the SMN axon pathfinding errors coincided with abnormal PMN axonal targeting in nicotine-exposed zebrafish. We conclude that nicotine exposure can exert differential effects depending on the levels of nicotine and developmental exposure window. - Highlights: • Embryonic nicotine exposure can specifically affect secondary motoneuron axons in a dose-dependent manner. �

Motoneuron axon pathfinding errors in zebrafish: Differential effects related to concentration and timing of nicotine exposure

Energy Technology Data Exchange (ETDEWEB)

Menelaou, Evdokia; Paul, Latoya T. [Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803 (United States); Perera, Surangi N. [Joseph J. Zilber School of Public Health, University of Wisconsin — Milwaukee, Milwaukee, WI 53205 (United States); Svoboda, Kurt R., E-mail: svobodak@uwm.edu [Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803 (United States); Joseph J. Zilber School of Public Health, University of Wisconsin — Milwaukee, Milwaukee, WI 53205 (United States)

2015-04-01

Nicotine exposure during embryonic stages of development can affect many neurodevelopmental processes. In the developing zebrafish, exposure to nicotine was reported to cause axonal pathfinding errors in the later born secondary motoneurons (SMNs). These alterations in SMN axon morphology coincided with muscle degeneration at high nicotine concentrations (15–30 μM). Previous work showed that the paralytic mutant zebrafish known as sofa potato exhibited nicotine-induced effects onto SMN axons at these high concentrations but in the absence of any muscle deficits, indicating that pathfinding errors could occur independent of muscle effects. In this study, we used varying concentrations of nicotine at different developmental windows of exposure to specifically isolate its effects onto subpopulations of motoneuron axons. We found that nicotine exposure can affect SMN axon morphology in a dose-dependent manner. At low concentrations of nicotine, SMN axons exhibited pathfinding errors, in the absence of any nicotine-induced muscle abnormalities. Moreover, the nicotine exposure paradigms used affected the 3 subpopulations of SMN axons differently, but the dorsal projecting SMN axons were primarily affected. We then identified morphologically distinct pathfinding errors that best described the nicotine-induced effects on dorsal projecting SMN axons. To test whether SMN pathfinding was potentially influenced by alterations in the early born primary motoneuron (PMN), we performed dual labeling studies, where both PMN and SMN axons were simultaneously labeled with antibodies. We show that only a subset of the SMN axon pathfinding errors coincided with abnormal PMN axonal targeting in nicotine-exposed zebrafish. We conclude that nicotine exposure can exert differential effects depending on the levels of nicotine and developmental exposure window. - Highlights: • Embryonic nicotine exposure can specifically affect secondary motoneuron axons in a dose-dependent manner. �

The decline and fall of Type II error rates

Science.gov (United States)

Steve Verrill; Mark Durst

2005-01-01

For general linear models with normally distributed random errors, the probability of a Type II error decreases exponentially as a function of sample size. This potentially rapid decline reemphasizes the importance of performing power calculations.

Perceptual learning eases crowding by reducing recognition errors but not position errors.

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Xiong, Ying-Zi; Yu, Cong; Zhang, Jun-Yun

2015-08-01

When an observer reports a letter flanked by additional letters in the visual periphery, the response errors (the crowding effect) may result from failure to recognize the target letter (recognition errors), from mislocating a correctly recognized target letter at a flanker location (target misplacement errors), or from reporting a flanker as the target letter (flanker substitution errors). Crowding can be reduced through perceptual learning. However, it is not known how perceptual learning operates to reduce crowding. In this study we trained observers with a partial-report task (Experiment 1), in which they reported the central target letter of a three-letter string presented in the visual periphery, or a whole-report task (Experiment 2), in which they reported all three letters in order. We then assessed the impact of training on recognition of both unflanked and flanked targets, with particular attention to how perceptual learning affected the types of errors. Our results show that training improved target recognition but not single-letter recognition, indicating that training indeed affected crowding. However, training did not reduce target misplacement errors or flanker substitution errors. This dissociation between target recognition and flanker substitution errors supports the view that flanker substitution may be more likely a by-product (due to response bias), rather than a cause, of crowding. Moreover, the dissociation is not consistent with hypothesized mechanisms of crowding that would predict reduced positional errors.

Inference on rare errors using asymptotic expansions and bootstrap calibration

NARCIS (Netherlands)

R. Helmers (Roelof)

1998-01-01

textabstractThe number of items in error in an audit population is usually quite small, whereas the error distribution is typically highly skewed to the right. For applications in statistical auditing, where line item sampling is appropriate, a new upper confidence limit for the total error amount

Putting a face on medical errors: a patient perspective.

Science.gov (United States)

Kooienga, Sarah; Stewart, Valerie T

2011-01-01

Knowledge of the patient's perspective on medical error is limited. Research efforts have centered on how best to disclose error and how patients desire to have medical error disclosed. On the basis of a qualitative descriptive component of a mixed method study, a purposive sample of 30 community members told their stories of medical error. Their experiences focused on lack of communication, missed communication, or provider's poor interpersonal style of communication, greatly contrasting with the formal definition of error as failure to follow a set standard of care. For these participants, being a patient was more important than error or how an error is disclosed. The patient's understanding of error must be a key aspect of any quality improvement strategy. © 2010 National Association for Healthcare Quality.

Teacher knowledge of error analysis in differential calculus

Directory of Open Access Journals (Sweden)

Eunice K. Moru

2014-12-01

Full Text Available The study investigated teacher knowledge of error analysis in differential calculus. Two teachers were the sample of the study: one a subject specialist and the other a mathematics education specialist. Questionnaires and interviews were used for data collection. The findings of the study reflect that the teachers’ knowledge of error analysis was characterised by the following assertions, which are backed up with some evidence: (1 teachers identified the errors correctly, (2 the generalised error identification resulted in opaque analysis, (3 some of the identified errors were not interpreted from multiple perspectives, (4 teachers’ evaluation of errors was either local or global and (5 in remedying errors accuracy and efficiency were emphasised more than conceptual understanding. The implications of the findings of the study for teaching include engaging in error analysis continuously as this is one way of improving knowledge for teaching.

Modeling Systematic Error Effects for a Sensitive Storage Ring EDM Polarimeter

Science.gov (United States)

Stephenson, Edward; Imig, Astrid

2009-10-01

The Storage Ring EDM Collaboration has obtained a set of measurements detailing the sensitivity of a storage ring polarimeter for deuterons to small geometrical and rate changes. Various schemes, such as the calculation of the cross ratio [1], can cancel effects due to detector acceptance differences and luminosity differences for states of opposite polarization. Such schemes fail at second-order in the errors, becoming sensitive to geometrical changes, polarization magnitude differences between opposite polarization states, and changes to the detector response with changing data rates. An expansion of the polarimeter response in a Taylor series based on small errors about the polarimeter operating point can parametrize such effects, primarily in terms of the logarithmic derivatives of the cross section and analyzing power. A comparison will be made to measurements obtained with the EDDA detector at COSY-J"ulich. [4pt] [1] G.G. Ohlsen and P.W. Keaton, Jr., NIM 109, 41 (1973).

Differential Effects of Visual-Acoustic Biofeedback Intervention for Residual Speech Errors

Science.gov (United States)

McAllister Byun, Tara; Campbell, Heather

2016-01-01

Recent evidence suggests that the incorporation of visual biofeedback technologies may enhance response to treatment in individuals with residual speech errors. However, there is a need for controlled research systematically comparing biofeedback versus non-biofeedback intervention approaches. This study implemented a single-subject experimental design with a crossover component to investigate the relative efficacy of visual-acoustic biofeedback and traditional articulatory treatment for residual rhotic errors. Eleven child/adolescent participants received ten sessions of visual-acoustic biofeedback and 10 sessions of traditional treatment, with the order of biofeedback and traditional phases counterbalanced across participants. Probe measures eliciting untreated rhotic words were administered in at least three sessions prior to the start of treatment (baseline), between the two treatment phases (midpoint), and after treatment ended (maintenance), as well as before and after each treatment session. Perceptual accuracy of rhotic production was assessed by outside listeners in a blinded, randomized fashion. Results were analyzed using a combination of visual inspection of treatment trajectories, individual effect sizes, and logistic mixed-effects regression. Effect sizes and visual inspection revealed that participants could be divided into categories of strong responders (n = 4), mixed/moderate responders (n = 3), and non-responders (n = 4). Individual results did not reveal a reliable pattern of stronger performance in biofeedback versus traditional blocks, or vice versa. Moreover, biofeedback versus traditional treatment was not a significant predictor of accuracy in the logistic mixed-effects model examining all within-treatment word probes. However, the interaction between treatment condition and treatment order was significant: biofeedback was more effective than traditional treatment in the first phase of treatment, and traditional treatment was more effective

A trend analysis of human error events for proactive prevention of accidents. Methodology development and effective utilization

International Nuclear Information System (INIS)

Hirotsu, Yuko; Ebisu, Mitsuhiro; Aikawa, Takeshi; Matsubara, Katsuyuki

2006-01-01

This paper described methods for analyzing human error events that has been accumulated in the individual plant and for utilizing the result to prevent accidents proactively. Firstly, a categorization framework of trigger action and causal factors of human error events were reexamined, and the procedure to analyze human error events was reviewed based on the framework. Secondly, a method for identifying the common characteristics of trigger action data and of causal factor data accumulated by analyzing human error events was clarified. In addition, to utilize the results of trend analysis effectively, methods to develop teaching material for safety education, to develop the checkpoints for the error prevention and to introduce an error management process for strategic error prevention were proposed. (author)

Sample Size Calculations for Population Size Estimation Studies Using Multiplier Methods With Respondent-Driven Sampling Surveys.

Science.gov (United States)

Fearon, Elizabeth; Chabata, Sungai T; Thompson, Jennifer A; Cowan, Frances M; Hargreaves, James R

2017-09-14

While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey. ©Elizabeth Fearon, Sungai T Chabata, Jennifer A Thompson, Frances M Cowan, James R Hargreaves. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2017.

Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

Science.gov (United States)

Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

2017-06-01

Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

Scaling prediction errors to reward variability benefits error-driven learning in humans.

Science.gov (United States)

Diederen, Kelly M J; Schultz, Wolfram

2015-09-01

Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influence of prediction error scaling and, in particular, the consequences for learning performance. Participants explicitly predicted reward magnitudes that were drawn from different probability distributions with specific standard deviations. By fitting the data with reinforcement learning models, we found scaling of prediction errors, in addition to the learning rate decay shown previously. Importantly, the prediction error scaling was closely related to learning performance, defined as accuracy in predicting the mean of reward distributions, across individual participants. In addition, participants who scaled prediction errors relative to standard deviation also presented with more similar performance for different standard deviations, indicating that increases in standard deviation did not substantially decrease "adapters'" accuracy in predicting the means of reward distributions. However, exaggerated scaling beyond the standard deviation resulted in impaired performance. Thus efficient adaptation makes learning more robust to changing variability. Copyright © 2015 the American Physiological Society.

Intraoperative visualization and assessment of electromagnetic tracking error

Science.gov (United States)

Harish, Vinyas; Ungi, Tamas; Lasso, Andras; MacDonald, Andrew; Nanji, Sulaiman; Fichtinger, Gabor

2015-03-01

Electromagnetic tracking allows for increased flexibility in designing image-guided interventions, however it is well understood that electromagnetic tracking is prone to error. Visualization and assessment of the tracking error should take place in the operating room with minimal interference with the clinical procedure. The goal was to achieve this ideal in an open-source software implementation in a plug and play manner, without requiring programming from the user. We use optical tracking as a ground truth. An electromagnetic sensor and optical markers are mounted onto a stylus device, pivot calibrated for both trackers. Electromagnetic tracking error is defined as difference of tool tip position between electromagnetic and optical readings. Multiple measurements are interpolated into the thin-plate B-spline transform visualized in real time using 3D Slicer. All tracked devices are used in a plug and play manner through the open-source SlicerIGT and PLUS extensions of the 3D Slicer platform. Tracking error was measured multiple times to assess reproducibility of the method, both with and without placing ferromagnetic objects in the workspace. Results from exhaustive grid sampling and freehand sampling were similar, indicating that a quick freehand sampling is sufficient to detect unexpected or excessive field distortion in the operating room. The software is available as a plug-in for the 3D Slicer platforms. Results demonstrate potential for visualizing electromagnetic tracking error in real time for intraoperative environments in feasibility clinical trials in image-guided interventions.

Effects of Yaw Error on Wind Turbine Running Characteristics Based on the Equivalent Wind Speed Model

Directory of Open Access Journals (Sweden)

Shuting Wan

2015-06-01

Full Text Available Natural wind is stochastic, being characterized by its speed and direction which change randomly and frequently. Because of the certain lag in control systems and the yaw body itself, wind turbines cannot be accurately aligned toward the wind direction when the wind speed and wind direction change frequently. Thus, wind turbines often suffer from a series of engineering issues during operation, including frequent yaw, vibration overruns and downtime. This paper aims to study the effects of yaw error on wind turbine running characteristics at different wind speeds and control stages by establishing a wind turbine model, yaw error model and the equivalent wind speed model that includes the wind shear and tower shadow effects. Formulas for the relevant effect coefficients Tc, Sc and Pc were derived. The simulation results indicate that the effects of the aerodynamic torque, rotor speed and power output due to yaw error at different running stages are different and that the effect rules for each coefficient are not identical when the yaw error varies. These results may provide theoretical support for optimizing the yaw control strategies for each stage to increase the running stability of wind turbines and the utilization rate of wind energy.

The Errors of Our Ways: Understanding Error Representations in Cerebellar-Dependent Motor Learning.

Science.gov (United States)

Popa, Laurentiu S; Streng, Martha L; Hewitt, Angela L; Ebner, Timothy J

2016-04-01

The cerebellum is essential for error-driven motor learning and is strongly implicated in detecting and correcting for motor errors. Therefore, elucidating how motor errors are represented in the cerebellum is essential in understanding cerebellar function, in general, and its role in motor learning, in particular. This review examines how motor errors are encoded in the cerebellar cortex in the context of a forward internal model that generates predictions about the upcoming movement and drives learning and adaptation. In this framework, sensory prediction errors, defined as the discrepancy between the predicted consequences of motor commands and the sensory feedback, are crucial for both on-line movement control and motor learning. While many studies support the dominant view that motor errors are encoded in the complex spike discharge of Purkinje cells, others have failed to relate complex spike activity with errors. Given these limitations, we review recent findings in the monkey showing that complex spike modulation is not necessarily required for motor learning or for simple spike adaptation. Also, new results demonstrate that the simple spike discharge provides continuous error signals that both lead and lag the actual movements in time, suggesting errors are encoded as both an internal prediction of motor commands and the actual sensory feedback. These dual error representations have opposing effects on simple spike discharge, consistent with the signals needed to generate sensory prediction errors used to update a forward internal model.

(AJST) RELATIVE EFFICIENCY OF NON-PARAMETRIC ERROR ...

African Journals Online (AJOL)

NORBERT OPIYO AKECH

on 100 bootstrap samples, a sample of size n being taken with replacement in each initial sample of size n. .... the overlap (or optimal error rate) of the populations. However, the expression (2.3) for the computation of ..... Analysis and Machine Intelligence, 9, 628-633. Lachenbruch P. A. (1967). An almost unbiased method ...

Ground-Wave Propagation Effects on Transmission Lines through Error Images

Directory of Open Access Journals (Sweden)

Uribe-Campos Felipe Alejandro

2014-07-01

Full Text Available Electromagnetic transient calculation of overhead transmission lines is strongly influenced by the natural resistivity of the ground. This varies from 1-10K (Ω·m depending on several media factors and on the physical composition of the ground. The accuracy on the calculation of a system transient response depends in part in the ground return model, which should consider the line geometry, the electrical resistivity and the frequency dependence of the power source. Up to date, there are only a few reports on the specialized literature about analyzing the effects produced by the presence of an imperfectly conducting ground of transmission lines in a transient state. A broad range analysis of three of the most often used ground-return models for calculating electromagnetic transients of overhead transmission lines is performed in this paper. The behavior of modal propagation in ground is analyzed here into effects of first and second order. Finally, a numerical tool based on relative error images is proposed in this paper as an aid for the analyst engineer to estimate the incurred error by using approximate ground-return models when calculating transients of overhead transmission lines.

Diagnostic errors in pediatric radiology

International Nuclear Information System (INIS)

Taylor, George A.; Voss, Stephan D.; Melvin, Patrice R.; Graham, Dionne A.

2011-01-01

Little information is known about the frequency, types and causes of diagnostic errors in imaging children. Our goals were to describe the patterns and potential etiologies of diagnostic error in our subspecialty. We reviewed 265 cases with clinically significant diagnostic errors identified during a 10-year period. Errors were defined as a diagnosis that was delayed, wrong or missed; they were classified as perceptual, cognitive, system-related or unavoidable; and they were evaluated by imaging modality and level of training of the physician involved. We identified 484 specific errors in the 265 cases reviewed (mean:1.8 errors/case). Most discrepancies involved staff (45.5%). Two hundred fifty-eight individual cognitive errors were identified in 151 cases (mean = 1.7 errors/case). Of these, 83 cases (55%) had additional perceptual or system-related errors. One hundred sixty-five perceptual errors were identified in 165 cases. Of these, 68 cases (41%) also had cognitive or system-related errors. Fifty-four system-related errors were identified in 46 cases (mean = 1.2 errors/case) of which all were multi-factorial. Seven cases were unavoidable. Our study defines a taxonomy of diagnostic errors in a large academic pediatric radiology practice and suggests that most are multi-factorial in etiology. Further study is needed to define effective strategies for improvement. (orig.)

Outcomes of a Failure Mode and Effects Analysis for medication errors in pediatric anesthesia.

Science.gov (United States)

Martin, Lizabeth D; Grigg, Eliot B; Verma, Shilpa; Latham, Gregory J; Rampersad, Sally E; Martin, Lynn D

2017-06-01

The Institute of Medicine has called for development of strategies to prevent medication errors, which are one important cause of preventable harm. Although the field of anesthesiology is considered a leader in patient safety, recent data suggest high medication error rates in anesthesia practice. Unfortunately, few error prevention strategies for anesthesia providers have been implemented. Using Toyota Production System quality improvement methodology, a multidisciplinary team observed 133 h of medication practice in the operating room at a tertiary care freestanding children's hospital. A failure mode and effects analysis was conducted to systematically deconstruct and evaluate each medication handling process step and score possible failure modes to quantify areas of risk. A bundle of five targeted countermeasures were identified and implemented over 12 months. Improvements in syringe labeling (73 to 96%), standardization of medication organization in the anesthesia workspace (0 to 100%), and two-provider infusion checks (23 to 59%) were observed. Medication error reporting improved during the project and was subsequently maintained. After intervention, the median medication error rate decreased from 1.56 to 0.95 per 1000 anesthetics. The frequency of medication error harm events reaching the patient also decreased. Systematic evaluation and standardization of medication handling processes by anesthesia providers in the operating room can decrease medication errors and improve patient safety. © 2017 John Wiley & Sons Ltd.

An estimate and evaluation of design error effects on nuclear power plant design adequacy

International Nuclear Information System (INIS)

Stevenson, J.D.

1984-01-01

An area of considerable concern in evaluating Design Control Quality Assurance procedures applied to design and analysis of nuclear power plant is the level of design error expected or encountered. There is very little published data 1 on the level of error typically found in nuclear power plant design calculations and even less on the impact such errors would be expected to have on overall design adequacy of the plant. This paper is concerned with design error associated with civil and mechanical structural design and analysis found in calculations which form part of the Design or Stress reports. These reports are meant to document the design basis and adequacy of the plant. The estimates contained in this paper are based on the personal experiences of the author. In Table 1 is a partial listing of the design docummentation review performed by the author on which the observations contained in this paper are based. In the preparation of any design calculations, it is a utopian dream to presume such calculations can be made error free. The intent of this paper is to define error levels which might be expected in a competent engineering organizations employing currently technically qualified engineers and accepted methods of Design Control. In addition, the effects of these errors on the probability of failure to meet applicable design code requirements also are estimated

Covariate measurement error correction methods in mediation analysis with failure time data.

Science.gov (United States)

Zhao, Shanshan; Prentice, Ross L

2014-12-01

Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This article focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error, and error associated with temporal variation. The underlying model with the "true" mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling designs. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. © 2014, The International Biometric Society.

Prevalence of technical errors and periapical lesions in a sample of endodontically treated teeth: a CBCT analysis.

Science.gov (United States)

Nascimento, Eduarda Helena Leandro; Gaêta-Araujo, Hugo; Andrade, Maria Fernanda Silva; Freitas, Deborah Queiroz

2018-01-21

The aims of this study are to identify the most frequent technical errors in endodontically treated teeth and to determine which root canals were most often associated with those errors, as well as to relate endodontic technical errors and the presence of coronal restorations with periapical status by means of cone-beam computed tomography images. Six hundred eighteen endodontically treated teeth (1146 root canals) were evaluated for the quality of their endodontic treatment and for the presence of coronal restorations and periapical lesions. Each root canal was classified according to dental groups, and the endodontic technical errors were recorded. Chi-square's test and descriptive analyses were performed. Six hundred eighty root canals (59.3%) had periapical lesions. Maxillary molars and anterior teeth showed higher prevalence of periapical lesions (p technical error in all root canals, except for the second mesiobuccal root canal of maxillary molars and the distobuccal root canal of mandibular molars, which were non-filled in 78.4 and 30% of the cases, respectively. There is a high prevalence of apical radiolucencies, which increased in the presence of poor coronal restorations, endodontic technical errors, and when both conditions were concomitant. Underfilling was the most frequent technical error, followed by non-homogeneous and non-filled canals. Evaluation of endodontic treatment quality that considers every single root canal aims on warning dental practitioners of the prevalence of technical errors that could be avoided with careful treatment planning and execution.

On a Test of Hypothesis to Verify the Operating Risk Due to Accountancy Errors

Directory of Open Access Journals (Sweden)

Paola Maddalena Chiodini

2014-12-01

Full Text Available According to the Statement on Auditing Standards (SAS No. 39 (AU 350.01, audit sampling is defined as “the application of an audit procedure to less than 100 % of the items within an account balance or class of transactions for the purpose of evaluating some characteristic of the balance or class”. The audit system develops in different steps: some are not susceptible to sampling procedures, while others may be held using sampling techniques. The auditor may also be interested in two types of accounting error: the number of incorrect records in the sample that overcome a given threshold (natural error rate, which may be indicative of possible fraud, and the mean amount of monetary errors found in incorrect records. The aim of this study is to monitor jointly both types of errors through an appropriate system of hypotheses, with particular attention to the second type error that indicates the risk of non-reporting errors overcoming the upper precision limits.

Effect of MLC leaf position, collimator rotation angle, and gantry rotation angle errors on intensity-modulated radiotherapy plans for nasopharyngeal carcinoma

Energy Technology Data Exchange (ETDEWEB)

Bai, Sen; Li, Guangjun; Wang, Maojie; Jiang, Qinfeng; Zhang, Yingjie [State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan (China); Wei, Yuquan, E-mail: yuquawei@vip.sina.com [State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan (China)

2013-07-01

The purpose of this study was to investigate the effect of multileaf collimator (MLC) leaf position, collimator rotation angle, and accelerator gantry rotation angle errors on intensity-modulated radiotherapy plans for nasopharyngeal carcinoma. To compare dosimetric differences between the simulating plans and the clinical plans with evaluation parameters, 6 patients with nasopharyngeal carcinoma were selected for simulation of systematic and random MLC leaf position errors, collimator rotation angle errors, and accelerator gantry rotation angle errors. There was a high sensitivity to dose distribution for systematic MLC leaf position errors in response to field size. When the systematic MLC position errors were 0.5, 1, and 2 mm, respectively, the maximum values of the mean dose deviation, observed in parotid glands, were 4.63%, 8.69%, and 18.32%, respectively. The dosimetric effect was comparatively small for systematic MLC shift errors. For random MLC errors up to 2 mm and collimator and gantry rotation angle errors up to 0.5°, the dosimetric effect was negligible. We suggest that quality control be regularly conducted for MLC leaves, so as to ensure that systematic MLC leaf position errors are within 0.5 mm. Because the dosimetric effect of 0.5° collimator and gantry rotation angle errors is negligible, it can be concluded that setting a proper threshold for allowed errors of collimator and gantry rotation angle may increase treatment efficacy and reduce treatment time.

Error begat error: design error analysis and prevention in social infrastructure projects.

Science.gov (United States)

Love, Peter E D; Lopez, Robert; Edwards, David J; Goh, Yang M

2012-09-01

Design errors contribute significantly to cost and schedule growth in social infrastructure projects and to engineering failures, which can result in accidents and loss of life. Despite considerable research that has addressed their error causation in construction projects they still remain prevalent. This paper identifies the underlying conditions that contribute to design errors in social infrastructure projects (e.g. hospitals, education, law and order type buildings). A systemic model of error causation is propagated and subsequently used to develop a learning framework for design error prevention. The research suggests that a multitude of strategies should be adopted in congruence to prevent design errors from occurring and so ensure that safety and project performance are ameliorated. Copyright © 2011. Published by Elsevier Ltd.

Predicting the outcomes of performance error indicators on accreditation status in the nuclear power industry

International Nuclear Information System (INIS)

Wilson, P.A.

1986-01-01

The null hypothesis for this study suggested that there was no significant difference in the types of performance error indicators between accredited and non-accredited programs on the following types of indicators: (1) number of significant event reports per unit, (2) number of forced outages per unit, (3) number of unplanned automatic scrams per unit, and (4) amount of equivalent availability per unit. A sample of 90 nuclear power plants was selected for this study. Data were summarized from two data bases maintained by the Institute of Nuclear Power Operations. Results of this study did not support the research hypothesis. There was no significant difference between the accredited and non-accredited programs on any of the four performance error indicators. The primary conclusions of this include the following: (1) The four selected performance error indicators cannot be used individually or collectively to predict accreditation status in the nuclear power industry. (2) Annual performance error indicator ratings cannot be used to determine the effects of performance-based training on plant performance. (3) The four selected performance error indicators cannot be used to measure the effect of operator job performance on plant effectiveness

Quantifying and handling errors in instrumental measurements using the measurement error theory

DEFF Research Database (Denmark)

Andersen, Charlotte Møller; Bro, R.; Brockhoff, P.B.

2003-01-01

. This is a new way of using the measurement error theory. Reliability ratios illustrate that the models for the two fish species are influenced differently by the error. However, the error seems to influence the predictions of the two reference measures in the same way. The effect of using replicated x...... measurements. A new general formula is given for how to correct the least squares regression coefficient when a different number of replicated x-measurements is used for prediction than for calibration. It is shown that the correction should be applied when the number of replicates in prediction is less than...

Effects of a direct refill program for automated dispensing cabinets on medication-refill errors.

Science.gov (United States)

Helmons, Pieter J; Dalton, Ashley J; Daniels, Charles E

2012-10-01

The effects of a direct refill program for automated dispensing cabinets (ADCs) on medication-refill errors were studied. This study was conducted in designated acute care areas of a 386-bed academic medical center. A wholesaler-to-ADC direct refill program, consisting of prepackaged delivery of medications and bar-code-assisted ADC refilling, was implemented in the inpatient pharmacy of the medical center in September 2009. Medication-refill errors in 26 ADCs from the general medicine units, the infant special care unit, the surgical and burn intensive care units, and intermediate units were assessed before and after the implementation of this program. Medication-refill errors were defined as an ADC pocket containing the wrong drug, wrong strength, or wrong dosage form. ADC refill errors decreased by 77%, from 62 errors per 6829 refilled pockets (0.91%) to 8 errors per 3855 refilled pockets (0.21%) (p error type detected before the intervention was the incorrect medication (wrong drug, wrong strength, or wrong dosage form) in the ADC pocket. Of the 54 incorrect medications found before the intervention, 38 (70%) were loaded in a multiple-drug drawer. After the implementation of the new refill process, 3 of the 5 incorrect medications were loaded in a multiple-drug drawer. There were 3 instances of expired medications before and only 1 expired medication after implementation of the program. A redesign of the ADC refill process using a wholesaler-to-ADC direct refill program that included delivery of prepackaged medication and bar-code-assisted refill significantly decreased the occurrence of ADC refill errors.

SYSTEMATIC ERROR REDUCTION: NON-TILTED REFERENCE BEAM METHOD FOR LONG TRACE PROFILER

International Nuclear Information System (INIS)

QIAN, S.; QIAN, K.; HONG, Y.; SENG, L.; HO, T.; TAKACS, P.

2007-01-01

Systematic error in the Long Trace Profiler (LTP) has become the major error source as measurement accuracy enters the nanoradian and nanometer regime. Great efforts have been made to reduce the systematic error at a number of synchrotron radiation laboratories around the world. Generally, the LTP reference beam has to be tilted away from the optical axis in order to avoid fringe overlap between the sample and reference beams. However, a tilted reference beam will result in considerable systematic error due to optical system imperfections, which is difficult to correct. Six methods of implementing a non-tilted reference beam in the LTP are introduced: (1) application of an external precision angle device to measure and remove slide pitch error without a reference beam, (2) independent slide pitch test by use of not tilted reference beam, (3) non-tilted reference test combined with tilted sample, (4) penta-prism scanning mode without a reference beam correction, (5) non-tilted reference using a second optical head, and (6) alternate switching of data acquisition between the sample and reference beams. With a non-tilted reference method, the measurement accuracy can be improved significantly. Some measurement results are presented. Systematic error in the sample beam arm is not addressed in this paper and should be treated separately

A flexible method for multi-level sample size determination

International Nuclear Information System (INIS)

Lu, Ming-Shih; Sanborn, J.B.; Teichmann, T.

1997-01-01

This paper gives a flexible method to determine sample sizes for both systematic and random error models (this pertains to sampling problems in nuclear safeguard questions). In addition, the method allows different attribute rejection limits. The new method could assist achieving a higher detection probability and enhance inspection effectiveness

Analysis of interactive fixed effects dynamic linear panel regression with measurement error

OpenAIRE

Nayoung Lee; Hyungsik Roger Moon; Martin Weidner

2011-01-01

This paper studies a simple dynamic panel linear regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method.

The effectiveness of cooling conditions on temperature of canine EDTA whole blood samples.

Science.gov (United States)

Tobias, Karen M; Serrano, Leslie; Sun, Xiaocun; Flatland, Bente

2016-01-01

Preanalytic factors such as time and temperature can have significant effects on laboratory test results. For example, ammonium concentration will increase 31% in blood samples stored at room temperature for 30 min before centrifugation. To reduce preanalytic error, blood samples may be placed in precooled tubes and chilled on ice or in ice water baths; however, the effectiveness of these modalities in cooling blood samples has not been formally evaluated. The purpose of this study was to evaluate the effectiveness of various cooling modalities on reducing temperature of EDTA whole blood samples. Pooled samples of canine EDTA whole blood were divided into two aliquots. Saline was added to one aliquot to produce a packed cell volume (PCV) of 40% and to the second aliquot to produce a PCV of 20% (simulated anemia). Thirty samples from each aliquot were warmed to 37.7 °C and cooled in 2 ml allotments under one of three conditions: in ice, in ice after transfer to a precooled tube, or in an ice water bath. Temperature of each sample was recorded at one minute intervals for 15 min. Within treatment conditions, sample PCV had no significant effect on cooling. Cooling in ice water was significantly faster than cooling in ice only or transferring the sample to a precooled tube and cooling it on ice. Mean temperature of samples cooled in ice water was significantly lower at 15 min than mean temperatures of those cooled in ice, whether or not the tube was precooled. By 4 min, samples cooled in an ice water bath had reached mean temperatures less than 4 °C (refrigeration temperature), while samples cooled in other conditions remained above 4.0 °C for at least 11 min. For samples with a PCV of 40%, precooling the tube had no significant effect on rate of cooling on ice. For samples with a PCV of 20%, transfer to a precooled tube resulted in a significantly faster rate of cooling than direct placement of the warmed tube onto ice. Canine EDTA whole blood samples cool most

The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study

Directory of Open Access Journals (Sweden)

Jamshid Jamali

2017-01-01

Full Text Available Evaluating measurement equivalence (also known as differential item functioning (DIF is an important part of the process of validating psychometric questionnaires. This study aimed at evaluating the multiple indicators multiple causes (MIMIC model for DIF detection when latent construct distribution is nonnormal and the focal group sample size is small. In this simulation-based study, Type I error rates and power of MIMIC model for detecting uniform-DIF were investigated under different combinations of reference to focal group sample size ratio, magnitude of the uniform-DIF effect, scale length, the number of response categories, and latent trait distribution. Moderate and high skewness in the latent trait distribution led to a decrease of 0.33% and 0.47% power of MIMIC model for detecting uniform-DIF, respectively. The findings indicated that, by increasing the scale length, the number of response categories and magnitude DIF improved the power of MIMIC model, by 3.47%, 4.83%, and 20.35%, respectively; it also decreased Type I error of MIMIC approach by 2.81%, 5.66%, and 0.04%, respectively. This study revealed that power of MIMIC model was at an acceptable level when latent trait distributions were skewed. However, empirical Type I error rate was slightly greater than nominal significance level. Consequently, the MIMIC was recommended for detection of uniform-DIF when latent construct distribution is nonnormal and the focal group sample size is small.

The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study.

Science.gov (United States)

Jamali, Jamshid; Ayatollahi, Seyyed Mohammad Taghi; Jafari, Peyman

2017-01-01

Evaluating measurement equivalence (also known as differential item functioning (DIF)) is an important part of the process of validating psychometric questionnaires. This study aimed at evaluating the multiple indicators multiple causes (MIMIC) model for DIF detection when latent construct distribution is nonnormal and the focal group sample size is small. In this simulation-based study, Type I error rates and power of MIMIC model for detecting uniform-DIF were investigated under different combinations of reference to focal group sample size ratio, magnitude of the uniform-DIF effect, scale length, the number of response categories, and latent trait distribution. Moderate and high skewness in the latent trait distribution led to a decrease of 0.33% and 0.47% power of MIMIC model for detecting uniform-DIF, respectively. The findings indicated that, by increasing the scale length, the number of response categories and magnitude DIF improved the power of MIMIC model, by 3.47%, 4.83%, and 20.35%, respectively; it also decreased Type I error of MIMIC approach by 2.81%, 5.66%, and 0.04%, respectively. This study revealed that power of MIMIC model was at an acceptable level when latent trait distributions were skewed. However, empirical Type I error rate was slightly greater than nominal significance level. Consequently, the MIMIC was recommended for detection of uniform-DIF when latent construct distribution is nonnormal and the focal group sample size is small.

Rovno Amber Ant Assamblage: Bias toward Arboreal Strata or Sampling Effect?

Directory of Open Access Journals (Sweden)

Perkovsky E. E.

2016-06-01

Full Text Available In 2015 B. Guenard with co-authors indicated that the Rovno amber ant assemblage, as described by G. Dlussky and A. Rasnitsyn (2009, showed modest support for a bias towards arboreal origin comparing the Baltic and Bitterfeld assemblages, although it is not clear whether this reflects a sampling error or a signal of real deviation. Since 2009, the Rovno ant collection has now grown more than twice in volume which makes possible to check if the above inference about the essentially arboreal character of the assemblage is real or due to a sampling error. The comparison provided suggests in favour of the latter reason for the bias revealed by B. Guenard and co-authors. The new and larger data on the Rovno assemblage show that the share of non-arboreal ants is now well comparable with those concerning the Baltic and Bitterfeld assemblages. This holds true for the both total assemblages and subassemblages of worker ants only.

Blood specimen labelling errors: Implications for nephrology nursing practice.

Science.gov (United States)

Duteau, Jennifer

2014-01-01

Patient safety is the foundation of high-quality health care, as recognized both nationally and worldwide. Patient blood specimen identification is critical in ensuring the delivery of safe and appropriate care. The practice of nephrology nursing involves frequent patient blood specimen withdrawals to treat and monitor kidney disease. A critical review of the literature reveals that incorrect patient identification is one of the major causes of blood specimen labelling errors. Misidentified samples create a serious risk to patient safety leading to multiple specimen withdrawals, delay in diagnosis, misdiagnosis, incorrect treatment, transfusion reactions, increased length of stay and other negative patient outcomes. Barcode technology has been identified as a preferred method for positive patient identification leading to a definitive decrease in blood specimen labelling errors by as much as 83% (Askeland, et al., 2008). The use of a root cause analysis followed by an action plan is one approach to decreasing the occurrence of blood specimen labelling errors. This article will present a review of the evidence-based literature surrounding blood specimen labelling errors, followed by author recommendations for completing a root cause analysis and action plan. A failure modes and effects analysis (FMEA) will be presented as one method to determine root cause, followed by the Ottawa Model of Research Use (OMRU) as a framework for implementation of strategies to reduce blood specimen labelling errors.

Functional heterogeneity of conflict, error, task-switching, and unexpectedness effects within medial prefrontal cortex.

Science.gov (United States)

Nee, Derek Evan; Kastner, Sabine; Brown, Joshua W

2011-01-01

The last decade has seen considerable discussion regarding a theoretical account of medial prefrontal cortex (mPFC) function with particular focus on the anterior cingulate cortex. The proposed theories have included conflict detection, error likelihood prediction, volatility monitoring, and several distinct theories of error detection. Arguments for and against particular theories often treat mPFC as functionally homogeneous, or at least nearly so, despite some evidence for distinct functional subregions. Here we used functional magnetic resonance imaging (fMRI) to simultaneously contrast multiple effects of error, conflict, and task-switching that have been individually construed in support of various theories. We found overlapping yet functionally distinct subregions of mPFC, with activations related to dominant error, conflict, and task-switching effects successively found along a rostral-ventral to caudal-dorsal gradient within medial prefrontal cortex. Activations in the rostral cingulate zone (RCZ) were strongly correlated with the unexpectedness of outcomes suggesting a role in outcome prediction and preparing control systems to deal with anticipated outcomes. The results as a whole support a resolution of some ongoing debates in that distinct theories may each pertain to corresponding distinct yet overlapping subregions of mPFC. Copyright © 2010 Elsevier Inc. All rights reserved.

Prevalence of Pre-Analytical Errors in Clinical Chemistry Diagnostic Labs in Sulaimani City of Iraqi Kurdistan.

Science.gov (United States)

Najat, Dereen

2017-01-01

Laboratory testing is roughly divided into three phases: a pre-analytical phase, an analytical phase and a post-analytical phase. Most analytical errors have been attributed to the analytical phase. However, recent studies have shown that up to 70% of analytical errors reflect the pre-analytical phase. The pre-analytical phase comprises all processes from the time a laboratory request is made by a physician until the specimen is analyzed at the lab. Generally, the pre-analytical phase includes patient preparation, specimen transportation, specimen collection and storage. In the present study, we report the first comprehensive assessment of the frequency and types of pre-analytical errors at the Sulaimani diagnostic labs in Iraqi Kurdistan. Over 2 months, 5500 venous blood samples were observed in 10 public diagnostic labs of Sulaimani City. The percentages of rejected samples and types of sample inappropriateness were evaluated. The percentage of each of the following pre-analytical errors were recorded: delay in sample transportation, clotted samples, expired reagents, hemolyzed samples, samples not on ice, incorrect sample identification, insufficient sample, tube broken in centrifuge, request procedure errors, sample mix-ups, communication conflicts, misinterpreted orders, lipemic samples, contaminated samples and missed physician's request orders. The difference between the relative frequencies of errors observed in the hospitals considered was tested using a proportional Z test. In particular, the survey aimed to discover whether analytical errors were recorded and examine the types of platforms used in the selected diagnostic labs. The analysis showed a high prevalence of improper sample handling during the pre-analytical phase. In appropriate samples, the percentage error was as high as 39%. The major reasons for rejection were hemolyzed samples (9%), incorrect sample identification (8%) and clotted samples (6%). Most quality control schemes at Sulaimani

Prevalence of Pre-Analytical Errors in Clinical Chemistry Diagnostic Labs in Sulaimani City of Iraqi Kurdistan.

Directory of Open Access Journals (Sweden)

Dereen Najat

Full Text Available Laboratory testing is roughly divided into three phases: a pre-analytical phase, an analytical phase and a post-analytical phase. Most analytical errors have been attributed to the analytical phase. However, recent studies have shown that up to 70% of analytical errors reflect the pre-analytical phase. The pre-analytical phase comprises all processes from the time a laboratory request is made by a physician until the specimen is analyzed at the lab. Generally, the pre-analytical phase includes patient preparation, specimen transportation, specimen collection and storage. In the present study, we report the first comprehensive assessment of the frequency and types of pre-analytical errors at the Sulaimani diagnostic labs in Iraqi Kurdistan.Over 2 months, 5500 venous blood samples were observed in 10 public diagnostic labs of Sulaimani City. The percentages of rejected samples and types of sample inappropriateness were evaluated. The percentage of each of the following pre-analytical errors were recorded: delay in sample transportation, clotted samples, expired reagents, hemolyzed samples, samples not on ice, incorrect sample identification, insufficient sample, tube broken in centrifuge, request procedure errors, sample mix-ups, communication conflicts, misinterpreted orders, lipemic samples, contaminated samples and missed physician's request orders. The difference between the relative frequencies of errors observed in the hospitals considered was tested using a proportional Z test. In particular, the survey aimed to discover whether analytical errors were recorded and examine the types of platforms used in the selected diagnostic labs.The analysis showed a high prevalence of improper sample handling during the pre-analytical phase. In appropriate samples, the percentage error was as high as 39%. The major reasons for rejection were hemolyzed samples (9%, incorrect sample identification (8% and clotted samples (6%. Most quality control schemes

Bayesian networks modeling for thermal error of numerical control machine tools

Institute of Scientific and Technical Information of China (English)

Xin-hua YAO; Jian-zhong FU; Zi-chen CHEN

2008-01-01

The interaction between the heat source location,its intensity,thermal expansion coefficient,the machine system configuration and the running environment creates complex thermal behavior of a machine tool,and also makes thermal error prediction difficult.To address this issue,a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented.The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques.Due to the effective combination of domain knowledge and sampled data,the BN method could adapt to the change of running state of machine,and obtain satisfactory prediction accuracy.Ex-periments on spindle thermal deformation were conducted to evaluate the modeling performance.Experimental results indicate that the BN method performs far better than the least squares(LS)analysis in terms of modeling estimation accuracy.

Detecting genotyping errors and describing black bear movement in northern Idaho

Science.gov (United States)

Michael K. Schwartz; Samuel A. Cushman; Kevin S. McKelvey; Jim Hayden; Cory Engkjer

2006-01-01

Non-invasive genetic sampling has become a favored tool to enumerate wildlife. Genetic errors, caused by poor quality samples, can lead to substantial biases in numerical estimates of individuals. We demonstrate how the computer program DROPOUT can detect amplification errors (false alleles and allelic dropout) in a black bear (Ursus americanus) dataset collected in...

How to Avoid Errors in Error Propagation: Prediction Intervals and Confidence Intervals in Forest Biomass

Science.gov (United States)

Lilly, P.; Yanai, R. D.; Buckley, H. L.; Case, B. S.; Woollons, R. C.; Holdaway, R. J.; Johnson, J.

2016-12-01

Calculations of forest biomass and elemental content require many measurements and models, each contributing uncertainty to the final estimates. While sampling error is commonly reported, based on replicate plots, error due to uncertainty in the regression used to estimate biomass from tree diameter is usually not quantified. Some published estimates of uncertainty due to the regression models have used the uncertainty in the prediction of individuals, ignoring uncertainty in the mean, while others have propagated uncertainty in the mean while ignoring individual variation. Using the simple case of the calcium concentration of sugar maple leaves, we compare the variation among individuals (the standard deviation) to the uncertainty in the mean (the standard error) and illustrate the declining importance in the prediction of individual concentrations as the number of individuals increases. For allometric models, the analogous statistics are the prediction interval (or the residual variation in the model fit) and the confidence interval (describing the uncertainty in the best fit model). The effect of propagating these two sources of error is illustrated using the mass of sugar maple foliage. The uncertainty in individual tree predictions was large for plots with few trees; for plots with 30 trees or more, the uncertainty in individuals was less important than the uncertainty in the mean. Authors of previously published analyses have reanalyzed their data to show the magnitude of these two sources of uncertainty in scales ranging from experimental plots to entire countries. The most correct analysis will take both sources of uncertainty into account, but for practical purposes, country-level reports of uncertainty in carbon stocks, as required by the IPCC, can ignore the uncertainty in individuals. Ignoring the uncertainty in the mean will lead to exaggerated estimates of confidence in estimates of forest biomass and carbon and nutrient contents.

Medication Errors: New EU Good Practice Guide on Risk Minimisation and Error Prevention.

Science.gov (United States)

Goedecke, Thomas; Ord, Kathryn; Newbould, Victoria; Brosch, Sabine; Arlett, Peter

2016-06-01

describes the key concepts of the EU good practice guidance for defining, classifying, coding, reporting, evaluating and preventing medication errors. This guidance should contribute to the safe and effective use of medicines for the benefit of patients and public health.

Large errors and severe conditions

CERN Document Server

Smith, D L; Van Wormer, L A

2002-01-01

Physical parameters that can assume real-number values over a continuous range are generally represented by inherently positive random variables. However, if the uncertainties in these parameters are significant (large errors), conventional means of representing and manipulating the associated variables can lead to erroneous results. Instead, all analyses involving them must be conducted in a probabilistic framework. Several issues must be considered: First, non-linear functional relations between primary and derived variables may lead to significant 'error amplification' (severe conditions). Second, the commonly used normal (Gaussian) probability distribution must be replaced by a more appropriate function that avoids the occurrence of negative sampling results. Third, both primary random variables and those derived through well-defined functions must be dealt with entirely in terms of their probability distributions. Parameter 'values' and 'errors' should be interpreted as specific moments of these probabil...

The effects of parameter estimation on minimizing the in-control average sample size for the double sampling X bar chart

Directory of Open Access Journals (Sweden)

Michael B.C. Khoo

2013-11-01

Full Text Available The double sampling (DS X bar chart, one of the most widely-used charting methods, is superior for detecting small and moderate shifts in the process mean. In a right skewed run length distribution, the median run length (MRL provides a more credible representation of the central tendency than the average run length (ARL, as the mean is greater than the median. In this paper, therefore, MRL is used as the performance criterion instead of the traditional ARL. Generally, the performance of the DS X bar chart is investigated under the assumption of known process parameters. In practice, these parameters are usually estimated from an in-control reference Phase-I dataset. Since the performance of the DS X bar chart is significantly affected by estimation errors, we study the effects of parameter estimation on the MRL-based DS X bar chart when the in-control average sample size is minimised. This study reveals that more than 80 samples are required for the MRL-based DS X bar chart with estimated parameters to perform more favourably than the corresponding chart with known parameters.

Positive phase error from parallel conductance in tetrapolar bio-impedance measurements and its compensation

Directory of Open Access Journals (Sweden)

Ivan M Roitt

2010-01-01

Full Text Available Bioimpedance measurements are of great use and can provide considerable insight into biological processes.  However, there are a number of possible sources of measurement error that must be considered.  The most dominant source of error is found in bipolar measurements where electrode polarisation effects are superimposed on the true impedance of the sample.  Even with the tetrapolar approach that is commonly used to circumvent this issue, other errors can persist. Here we characterise the positive phase and rise in impedance magnitude with frequency that can result from the presence of any parallel conductive pathways in the measurement set-up.  It is shown that fitting experimental data to an equivalent electrical circuit model allows for accurate determination of the true sample impedance as validated through finite element modelling (FEM of the measurement chamber.  Finally, the model is used to extract dispersion information from cell cultures to characterise their growth.

Architecture design for soft errors

CERN Document Server

Mukherjee, Shubu

2008-01-01

This book provides a comprehensive description of the architetural techniques to tackle the soft error problem. It covers the new methodologies for quantitative analysis of soft errors as well as novel, cost-effective architectural techniques to mitigate them. To provide readers with a better grasp of the broader problem deffinition and solution space, this book also delves into the physics of soft errors and reviews current circuit and software mitigation techniques.

Dual-energy X-ray absorptiometry: analysis of pediatric fat estimate errors due to tissue hydration effects.

Science.gov (United States)

Testolin, C G; Gore, R; Rivkin, T; Horlick, M; Arbo, J; Wang, Z; Chiumello, G; Heymsfield, S B

2000-12-01

Dual-energy X-ray absorptiometry (DXA) percent (%) fat estimates may be inaccurate in young children, who typically have high tissue hydration levels. This study was designed to provide a comprehensive analysis of pediatric tissue hydration effects on DXA %fat estimates. Phase 1 was experimental and included three in vitro studies to establish the physical basis of DXA %fat-estimation models. Phase 2 extended phase 1 models and consisted of theoretical calculations to estimate the %fat errors emanating from previously reported pediatric hydration effects. Phase 1 experiments supported the two-compartment DXA soft tissue model and established that pixel ratio of low to high energy (R values) are a predictable function of tissue elemental content. In phase 2, modeling of reference body composition values from birth to age 120 mo revealed that %fat errors will arise if a "constant" adult lean soft tissue R value is applied to the pediatric population; the maximum %fat error, approximately 0.8%, would be present at birth. High tissue hydration, as observed in infants and young children, leads to errors in DXA %fat estimates. The magnitude of these errors based on theoretical calculations is small and may not be of clinical or research significance.

Terrestrial neutron-induced soft errors in advanced memory devices

CERN Document Server

Nakamura, Takashi; Ibe, Eishi; Yahagi, Yasuo; Kameyama, Hideaki

2008-01-01

Terrestrial neutron-induced soft errors in semiconductor memory devices are currently a major concern in reliability issues. Understanding the mechanism and quantifying soft-error rates are primarily crucial for the design and quality assurance of semiconductor memory devices. This book covers the relevant up-to-date topics in terrestrial neutron-induced soft errors, and aims to provide succinct knowledge on neutron-induced soft errors to the readers by presenting several valuable and unique features. Sample Chapter(s). Chapter 1: Introduction (238 KB). Table A.30 mentioned in Appendix A.6 on

Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples

Energy Technology Data Exchange (ETDEWEB)

Shine, E. P.; Poirier, M. R.

2013-10-29

Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and data interpretation and reporting that considers the uncertainty of all error sources. Numerous sampling studies were conducted during the development of the DWPF process and still continue to be performed in order to evaluate options for process improvement. Study designs were based on use of statistical tools applicable to the determination of uncertainties associated with the data needs. Successful designs are apt to be repeated, so this report chose only to include prototypic case studies that typify the characteristics of frequently used designs. Case studies have been presented for studying in-tank homogeneity, evaluating the suitability of sampler systems, determining factors that affect mixing and sampling, comparing the final waste glass product chemical composition and durability to that of the glass pour stream sample and other samples from process vessels, and assessing the uniformity of the chemical composition in the waste glass product. Many of these studies efficiently addressed more than one of these areas of concern associated with demonstrating sample representativeness and provide examples of statistical tools in use for DWPF. The time when many of these designs were implemented was in an age when the sampling ideas of Pierre Gy were not as widespread as they are today. Nonetheless, the engineers and

Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples

International Nuclear Information System (INIS)

Shine, E. P.; Poirier, M. R.

2013-01-01

Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and data interpretation and reporting that considers the uncertainty of all error sources. Numerous sampling studies were conducted during the development of the DWPF process and still continue to be performed in order to evaluate options for process improvement. Study designs were based on use of statistical tools applicable to the determination of uncertainties associated with the data needs. Successful designs are apt to be repeated, so this report chose only to include prototypic case studies that typify the characteristics of frequently used designs. Case studies have been presented for studying in-tank homogeneity, evaluating the suitability of sampler systems, determining factors that affect mixing and sampling, comparing the final waste glass product chemical composition and durability to that of the glass pour stream sample and other samples from process vessels, and assessing the uniformity of the chemical composition in the waste glass product. Many of these studies efficiently addressed more than one of these areas of concern associated with demonstrating sample representativeness and provide examples of statistical tools in use for DWPF. The time when many of these designs were implemented was in an age when the sampling ideas of Pierre Gy were not as widespread as they are today. Nonetheless, the engineers and

Errors in patient specimen collection: application of statistical process control.

Science.gov (United States)

Dzik, Walter Sunny; Beckman, Neil; Selleng, Kathleen; Heddle, Nancy; Szczepiorkowski, Zbigniew; Wendel, Silvano; Murphy, Michael

2008-10-01

Errors in the collection and labeling of blood samples for pretransfusion testing increase the risk of transfusion-associated patient morbidity and mortality. Statistical process control (SPC) is a recognized method to monitor the performance of a critical process. An easy-to-use SPC method was tested to determine its feasibility as a tool for monitoring quality in transfusion medicine. SPC control charts were adapted to a spreadsheet presentation. Data tabulating the frequency of mislabeled and miscollected blood samples from 10 hospitals in five countries from 2004 to 2006 were used to demonstrate the method. Control charts were produced to monitor process stability. The participating hospitals found the SPC spreadsheet very suitable to monitor the performance of the sample labeling and collection and applied SPC charts to suit their specific needs. One hospital monitored subcategories of sample error in detail. A large hospital monitored the number of wrong-blood-in-tube (WBIT) events. Four smaller-sized facilities, each following the same policy for sample collection, combined their data on WBIT samples into a single control chart. One hospital used the control chart to monitor the effect of an educational intervention. A simple SPC method is described that can monitor the process of sample collection and labeling in any hospital. SPC could be applied to other critical steps in the transfusion processes as a tool for biovigilance and could be used to develop regional or national performance standards for pretransfusion sample collection. A link is provided to download the spreadsheet for free.

Prediction-error variance in Bayesian model updating: a comparative study

Science.gov (United States)

Asadollahi, Parisa; Li, Jian; Huang, Yong

2017-04-01

In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model

How Sample Size Affects a Sampling Distribution

Science.gov (United States)

Mulekar, Madhuri S.; Siegel, Murray H.

2009-01-01

If students are to understand inferential statistics successfully, they must have a profound understanding of the nature of the sampling distribution. Specifically, they must comprehend the determination of the expected value and standard error of a sampling distribution as well as the meaning of the central limit theorem. Many students in a high…

Medical Error and Moral Luck.

Science.gov (United States)

Hubbeling, Dieneke

2016-09-01

This paper addresses the concept of moral luck. Moral luck is discussed in the context of medical error, especially an error of omission that occurs frequently, but only rarely has adverse consequences. As an example, a failure to compare the label on a syringe with the drug chart results in the wrong medication being administered and the patient dies. However, this error may have previously occurred many times with no tragic consequences. Discussions on moral luck can highlight conflicting intuitions. Should perpetrators receive a harsher punishment because of an adverse outcome, or should they be dealt with in the same way as colleagues who have acted similarly, but with no adverse effects? An additional element to the discussion, specifically with medical errors, is that according to the evidence currently available, punishing individual practitioners does not seem to be effective in preventing future errors. The following discussion, using relevant philosophical and empirical evidence, posits a possible solution for the moral luck conundrum in the context of medical error: namely, making a distinction between the duty to make amends and assigning blame. Blame should be assigned on the basis of actual behavior, while the duty to make amends is dependent on the outcome.

[Study on the Effects and Compensation Effect of Recording Parameters Error on Imaging Performance of Holographic Grating in On-Line Spectral Diagnose].

Science.gov (United States)

Jiang, Yan-xiu; Bayanheshig; Yang, Shuo; Zhao, Xu-long; Wu, Na; Li, Wen-hao

2016-03-01

To making the high resolution grating, a numerical calculation was used to analyze the effect of recording parameters on groove density, focal curve and imaging performance of the grating and their compensation. Based on Fermat' s principle, light path function and aberration, the effect on imaging performance of the grating was analyzed. In the case of fixed using parameters, the error of the recording angle has a greater influence on imaging performance, therefore the gain of the weight of recording angle can improve the accuracy of the recording angle values in the optimization; recording distance has little influence on imaging performance; the relative errors of recording parameters cause the change of imaging performance of the grating; the results indicate that recording parameter errors can be compensated by adjusting its corresponding parameter. The study can give theoretical guidance to the fabrication for high resolution varied-line-space plane holographic grating in on-line spectral diagnostic and reduce the alignment difficulty by analyze the main error effect the imaging performance and propose the compensation method.

Artificial neural network implementation of a near-ideal error prediction controller

Science.gov (United States)

Mcvey, Eugene S.; Taylor, Lynore Denise

1992-01-01

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error

Different grades MEMS accelerometers error characteristics

Science.gov (United States)

Pachwicewicz, M.; Weremczuk, J.

2017-08-01

The paper presents calibration effects of two different MEMS accelerometers of different price and quality grades and discusses different accelerometers errors types. The calibration for error determining is provided by reference centrifugal measurements. The design and measurement errors of the centrifuge are discussed as well. It is shown that error characteristics of the sensors are very different and it is not possible to use simple calibration methods presented in the literature in both cases.

Medical error identification, disclosure, and reporting: do emergency medicine provider groups differ?

Science.gov (United States)

Hobgood, Cherri; Weiner, Bryan; Tamayo-Sarver, Joshua H

2006-04-01

To determine if the three types of emergency medicine providers--physicians, nurses, and out-of-hospital providers (emergency medical technicians [EMTs])--differ in their identification, disclosure, and reporting of medical error. A convenience sample of providers in an academic emergency department evaluated ten case vignettes that represented two error types (medication and cognitive) and three severity levels. For each vignette, providers were asked the following: 1) Is this an error? 2) Would you tell the patient? 3) Would you report this to a hospital committee? To assess differences in identification, disclosure, and reporting by provider type, error type, and error severity, the authors constructed three-way tables with the nonparametric Somers' D clustered on participant. To assess the contribution of disclosure instruction and environmental variables, fixed-effects regression stratified by provider type was used. Of the 116 providers who were eligible, 103 (40 physicians, 26 nurses, and 35 EMTs) had complete data. Physicians were more likely to classify an event as an error (78%) than nurses (71%; p = 0.04) or EMTs (68%; p error to the patient (59%) than physicians (71%; p = 0.04). Physicians were the least likely to report the error (54%) compared with nurses (68%; p = 0.02) or EMTs (78%; p error types, identification, disclosure, and reporting increased with increasing severity. Improving patient safety hinges on the ability of health care providers to accurately identify, disclose, and report medical errors. Interventions must account for differences in error identification, disclosure, and reporting by provider type.

Spelling Errors of Iranian School-Level EFL Learners: Potential Sources

Directory of Open Access Journals (Sweden)

Mahnaz Saeidi

2010-05-01

Full Text Available With the purpose of examining the sources of spelling errors of Iranian school level EFL learners, the present researchers analyzed the dictation samples of 51 Iranian senior and junior high school male and female students majoring at an Iranian school in Baku, Azerbaijan. The content analysis of the data revealed three main sources (intralingual, interlingual, and unique with seven patterns of errors. The frequency of intralingual errors far outnumbers that of interlingual errors. Unique errors were even less. Therefore, in-service training programs may include some instruction on raising the teachers’ awareness of the different sources of errors to focus on during the teaching program.

Internal consistency, test-retest reliability and measurement error of the self-report version of the social skills rating system in a sample of Australian adolescents.

Directory of Open Access Journals (Sweden)

Sharmila Vaz

Full Text Available The social skills rating system (SSRS is used to assess social skills and competence in children and adolescents. While its characteristics based on United States samples (US are published, corresponding Australian figures are unavailable. Using a 4-week retest design, we examined the internal consistency, retest reliability and measurement error (ME of the SSRS secondary student form (SSF in a sample of Year 7 students (N = 187, from five randomly selected public schools in Perth, western Australia. Internal consistency (IC of the total scale and most subscale scores (except empathy on the frequency rating scale was adequate to permit independent use. On the importance rating scale, most IC estimates for girls fell below the benchmark. Test-retest estimates of the total scale and subscales were insufficient to permit reliable use. ME of the total scale score (frequency rating for boys was equivalent to the US estimate, while that for girls was lower than the US error. ME of the total scale score (importance rating was larger than the error using the frequency rating scale. The study finding supports the idea of using multiple informants (e.g. teacher and parent reports, not just student as recommended in the manual. Future research needs to substantiate the clinical meaningfulness of the MEs calculated in this study by corroborating them against the respective Minimum Clinically Important Difference (MCID.

Internal consistency, test-retest reliability and measurement error of the self-report version of the social skills rating system in a sample of Australian adolescents.

Science.gov (United States)

Vaz, Sharmila; Parsons, Richard; Passmore, Anne Elizabeth; Andreou, Pantelis; Falkmer, Torbjörn

2013-01-01

The social skills rating system (SSRS) is used to assess social skills and competence in children and adolescents. While its characteristics based on United States samples (US) are published, corresponding Australian figures are unavailable. Using a 4-week retest design, we examined the internal consistency, retest reliability and measurement error (ME) of the SSRS secondary student form (SSF) in a sample of Year 7 students (N = 187), from five randomly selected public schools in Perth, western Australia. Internal consistency (IC) of the total scale and most subscale scores (except empathy) on the frequency rating scale was adequate to permit independent use. On the importance rating scale, most IC estimates for girls fell below the benchmark. Test-retest estimates of the total scale and subscales were insufficient to permit reliable use. ME of the total scale score (frequency rating) for boys was equivalent to the US estimate, while that for girls was lower than the US error. ME of the total scale score (importance rating) was larger than the error using the frequency rating scale. The study finding supports the idea of using multiple informants (e.g. teacher and parent reports), not just student as recommended in the manual. Future research needs to substantiate the clinical meaningfulness of the MEs calculated in this study by corroborating them against the respective Minimum Clinically Important Difference (MCID).

Did I Do That? Expectancy Effects of Brain Stimulation on Error-related Negativity and Sense of Agency.

Science.gov (United States)

Hoogeveen, Suzanne; Schjoedt, Uffe; van Elk, Michiel

2018-06-19

This study examines the effects of expected transcranial stimulation on the error(-related) negativity (Ne or ERN) and the sense of agency in participants who perform a cognitive control task. Placebo transcranial direct current stimulation was used to elicit expectations of transcranially induced cognitive improvement or impairment. The improvement/impairment manipulation affected both the Ne/ERN and the sense of agency (i.e., whether participants attributed errors to oneself or the brain stimulation device): Expected improvement increased the ERN in response to errors compared with both impairment and control conditions. Expected impairment made participants falsely attribute errors to the transcranial stimulation. This decrease in sense of agency was correlated with a reduced ERN amplitude. These results show that expectations about transcranial stimulation impact users' neural response to self-generated errors and the attribution of responsibility-especially when actions lead to negative outcomes. We discuss our findings in relation to predictive processing theory according to which the effect of prior expectations on the ERN reflects the brain's attempt to generate predictive models of incoming information. By demonstrating that induced expectations about transcranial stimulation can have effects at a neural level, that is, beyond mere demand characteristics, our findings highlight the potential for placebo brain stimulation as a promising tool for research.

Putting into practice error management theory: Unlearning and learning to manage action errors in construction.

Science.gov (United States)

Love, Peter E D; Smith, Jim; Teo, Pauline

2018-05-01

Error management theory is drawn upon to examine how a project-based organization, which took the form of a program alliance, was able to change its established error prevention mindset to one that enacted a learning mindfulness that provided an avenue to curtail its action errors. The program alliance was required to unlearn its existing routines and beliefs to accommodate the practices required to embrace error management. As a result of establishing an error management culture the program alliance was able to create a collective mindfulness that nurtured learning and supported innovation. The findings provide a much-needed context to demonstrate the relevance of error management theory to effectively address rework and safety problems in construction projects. The robust theoretical underpinning that is grounded in practice and presented in this paper provides a mechanism to engender learning from errors, which can be utilized by construction organizations to improve the productivity and performance of their projects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effect of video decoder errors on video interpretability

Science.gov (United States)

Young, Darrell L.

2014-06-01

The advancement in video compression technology can result in more sensitivity to bit errors. Bit errors can propagate causing sustained loss of interpretability. In the worst case, the decoder "freezes" until it can re-synchronize with the stream. Detection of artifacts enables downstream processes to avoid corrupted frames. A simple template approach to detect block stripes and a more advanced cascade approach to detect compression artifacts was shown to correlate to the presence of artifacts and decoder messages.

Support, shape and number of replicate samples for tree foliage analysis

NARCIS (Netherlands)

Luyssaert, Sebastiaan; Mertens, Jan; Raitio, Hannu

Many fundamental features of a sampling program are determined by the heterogeneity of the object under study and the settings for the error (α), the power (β), the effect size (ES), the number of replicate samples, and sample support, which is a feature that is often overlooked. The number of

Intra- and interobserver error of the Greulich-Pyle method as used on a Danish forensic sample

DEFF Research Database (Denmark)

Lynnerup, N; Belard, E; Buch-Olsen, K

2008-01-01

that atlas-based techniques are obsolete and ought to be replaced by other methods. Specifically, the GPA test sample consisted of American "white" children "above average in economic and educational status", leading to the question as to how comparable subjects being scored by the GPA method today...... and intraoral dental radiographs. Different methods are used depending on the maturity of the individual examined; and (3) a carpal X-ray examination, using the Greulich and Pyle Atlas (GPA) method. We present the results of intra- and interobserver tests of carpal X-rays in blind trials, and a comparison...... of the age estimations by carpal X-rays and odontological age estimation. We retrieved 159 cases from the years 2000-2002 (inclusive). The intra- and interobserver errors are overall small. We found full agreement in 126/159 cases, and this was between experienced users and novices. Overall, the mean...

A 2 × 2 taxonomy of multilevel latent contextual models: accuracy-bias trade-offs in full and partial error correction models.

Science.gov (United States)

Lüdtke, Oliver; Marsh, Herbert W; Robitzsch, Alexander; Trautwein, Ulrich

2011-12-01

In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data when estimating contextual effects are distinguished: unreliability that is due to measurement error and unreliability that is due to sampling error. The fact that studies may or may not correct for these 2 types of error can be translated into a 2 × 2 taxonomy of multilevel latent contextual models comprising 4 approaches: an uncorrected approach, partial correction approaches correcting for either measurement or sampling error (but not both), and a full correction approach that adjusts for both sources of error. It is shown mathematically and with simulated data that the uncorrected and partial correction approaches can result in substantially biased estimates of contextual effects, depending on the number of L1 individuals per group, the number of groups, the intraclass correlation, the number of indicators, and the size of the factor loadings. However, the simulation study also shows that partial correction approaches can outperform full correction approaches when the data provide only limited information in terms of the L2 construct (i.e., small number of groups, low intraclass correlation). A real-data application from educational psychology is used to illustrate the different approaches.

Systematic and non-systematic effects of the uncertainty of the sample position in gamma-ray spectrometry

International Nuclear Information System (INIS)

Vidmar, T.; Korun, M.

2004-01-01

When cylindrical samples placed coaxially with the detector are measured on a gamma-ray spectrometer, the position of the sample very often deviates from an ideal one with the axes of the sample and the detector less than perfectly aligned. If a calibrated source is used prior to the measurement and is presumed to have been positioned correctly, one might conclude that the misalignment of the measured sample should result in an uncertainty of the reported nuclide activity, since the efficiencies of the sample and the calibrated source are effectively different due to the difference in placement. The efficiency of a displaced cylindrical sample, however, is always lower than the one of a sample that is perfectly aligned. The net effect of misalignment can therefore be not only an increase in the uncertainty of the activity, but also a systematic error in its evaluation. Since the Guide to the Expression of Uncertainty in Measurement requires that all such systematic effects be corrected for, we have developed a method to assess the change in the efficiency resulting from misalignment and to introduce the required correction. The calculation of this correction only requires knowledge of basic sample and detector data. The uncertainty of the reported activity can then also be assessed and is influenced by the uncertainty of the efficiency evaluated around its new, corrected value. An appropriate expression for this uncertainty has been derived

Error Control in Distributed Node Self-Localization

Directory of Open Access Journals (Sweden)

Ying Zhang

2008-03-01

Full Text Available Location information of nodes in an ad hoc sensor network is essential to many tasks such as routing, cooperative sensing, and service delivery. Distributed node self-localization is lightweight and requires little communication overhead, but often suffers from the adverse effects of error propagation. Unlike other localization papers which focus on designing elaborate localization algorithms, this paper takes a different perspective, focusing on the error propagation problem, addressing questions such as where localization error comes from and how it propagates from node to node. To prevent error from propagating and accumulating, we develop an error-control mechanism based on characterization of node uncertainties and discrimination between neighboring nodes. The error-control mechanism uses only local knowledge and is fully decentralized. Simulation results have shown that the active selection strategy significantly mitigates the effect of error propagation for both range and directional sensors. It greatly improves localization accuracy and robustness.

Estimation of Total Error in DWPF Reported Radionuclide Inventories

International Nuclear Information System (INIS)

Edwards, T.B.

1995-01-01

This report investigates the impact of random errors due to measurement and sampling on the reported concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch. The objective of this investigation is to estimate the variance of the total error in reporting these radionuclide concentrations

Error-source effects on the performance of direct and iterative algorithms on an optical matrix-vector processor

Science.gov (United States)

Perlee, Caroline J.; Casasent, David P.

1990-09-01

Error sources in an optical matrix-vector processor are analyzed in terms of their effect on the performance of the algorithms used to solve a set of nonlinear and linear algebraic equations. A direct and an iterative algorithm are used to solve a nonlinear time-dependent case-study from computational fluid dynamics. A simulator which emulates the data flow and number representation of the OLAP is used to studs? these error effects. The ability of each algorithm to tolerate or correct the error sources is quantified. These results are extended to the general case of solving nonlinear and linear algebraic equations on the optical system.

Organizational safety culture and medical error reporting by Israeli nurses.

Science.gov (United States)

Kagan, Ilya; Barnoy, Sivia

2013-09-01

To investigate the association between patient safety culture (PSC) and the incidence and reporting rate of medical errors by Israeli nurses. Self-administered structured questionnaires were distributed to a convenience sample of 247 registered nurses enrolled in training programs at Tel Aviv University (response rate = 91%). The questionnaire's three sections examined the incidence of medication mistakes in clinical practice, the reporting rate for these errors, and the participants' views and perceptions of the safety culture in their workplace at three levels (organizational, departmental, and individual performance). Pearson correlation coefficients, t tests, and multiple regression analysis were used to analyze the data. Most nurses encountered medical errors from a daily to a weekly basis. Six percent of the sample never reported their own errors, while half reported their own errors "rarely or sometimes." The level of PSC was positively and significantly correlated with the error reporting rate. PSC, place of birth, error incidence, and not having an academic nursing degree were significant predictors of error reporting, together explaining 28% of variance. This study confirms the influence of an organizational safety climate on readiness to report errors. Senior healthcare executives and managers can make a major impact on safety culture development by creating and promoting a vision and strategy for quality and safety and fostering their employees' motivation to implement improvement programs at the departmental and individual level. A positive, carefully designed organizational safety culture can encourage error reporting by staff and so improve patient safety. © 2013 Sigma Theta Tau International.

NLO error propagation exercise: statistical results

International Nuclear Information System (INIS)

Pack, D.J.; Downing, D.J.

1985-09-01

Error propagation is the extrapolation and cumulation of uncertainty (variance) above total amounts of special nuclear material, for example, uranium or 235 U, that are present in a defined location at a given time. The uncertainty results from the inevitable inexactness of individual measurements of weight, uranium concentration, 235 U enrichment, etc. The extrapolated and cumulated uncertainty leads directly to quantified limits of error on inventory differences (LEIDs) for such material. The NLO error propagation exercise was planned as a field demonstration of the utilization of statistical error propagation methodology at the Feed Materials Production Center in Fernald, Ohio from April 1 to July 1, 1983 in a single material balance area formed specially for the exercise. Major elements of the error propagation methodology were: variance approximation by Taylor Series expansion; variance cumulation by uncorrelated primary error sources as suggested by Jaech; random effects ANOVA model estimation of variance effects (systematic error); provision for inclusion of process variance in addition to measurement variance; and exclusion of static material. The methodology was applied to material balance area transactions from the indicated time period through a FORTRAN computer code developed specifically for this purpose on the NLO HP-3000 computer. This paper contains a complete description of the error propagation methodology and a full summary of the numerical results of applying the methodlogy in the field demonstration. The error propagation LEIDs did encompass the actual uranium and 235 U inventory differences. Further, one can see that error propagation actually provides guidance for reducing inventory differences and LEIDs in future time periods

Analysis of the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery☆

Science.gov (United States)

Arba-Mosquera, Samuel; Aslanides, Ioannis M.

2012-01-01

Purpose To analyze the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery. Methods A comprehensive model, which directly considers eye movements, including saccades, vestibular, optokinetic, vergence, and miniature, as well as, eye-tracker acquisition rate, eye-tracker latency time, scanner positioning time, laser firing rate, and laser trigger delay have been developed. Results Eye-tracker acquisition rates below 100 Hz correspond to pulse positioning errors above 1.5 mm. Eye-tracker latency times to about 15 ms correspond to pulse positioning errors of up to 3.5 mm. Scanner positioning times to about 9 ms correspond to pulse positioning errors of up to 2 mm. Laser firing rates faster than eye-tracker acquisition rates basically duplicate pulse-positioning errors. Laser trigger delays to about 300 μs have minor to no impact on pulse-positioning errors. Conclusions The proposed model can be used for comparison of laser systems used for ablation processes. Due to the pseudo-random nature of eye movements, positioning errors of single pulses are much larger than observed decentrations in the clinical settings. There is no single parameter that ‘alone’ minimizes the positioning error. It is the optimal combination of the several parameters that minimizes the error. The results of this analysis are important to understand the limitations of correcting very irregular ablation patterns.

Dopamine reward prediction error coding.

Science.gov (United States)

Schultz, Wolfram

2016-03-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

Soft error mechanisms, modeling and mitigation

CERN Document Server

Sayil, Selahattin

2016-01-01

This book introduces readers to various radiation soft-error mechanisms such as soft delays, radiation induced clock jitter and pulses, and single event (SE) coupling induced effects. In addition to discussing various radiation hardening techniques for combinational logic, the author also describes new mitigation strategies targeting commercial designs. Coverage includes novel soft error mitigation techniques such as the Dynamic Threshold Technique and Soft Error Filtering based on Transmission gate with varied gate and body bias. The discussion also includes modeling of SE crosstalk noise, delay and speed-up effects. Various mitigation strategies to eliminate SE coupling effects are also introduced. Coverage also includes the reliability of low power energy-efficient designs and the impact of leakage power consumption optimizations on soft error robustness. The author presents an analysis of various power optimization techniques, enabling readers to make design choices that reduce static power consumption an...

Apologies and Medical Error

Science.gov (United States)

2008-01-01

One way in which physicians can respond to a medical error is to apologize. Apologies—statements that acknowledge an error and its consequences, take responsibility, and communicate regret for having caused harm—can decrease blame, decrease anger, increase trust, and improve relationships. Importantly, apologies also have the potential to decrease the risk of a medical malpractice lawsuit and can help settle claims by patients. Patients indicate they want and expect explanations and apologies after medical errors and physicians indicate they want to apologize. However, in practice, physicians tend to provide minimal information to patients after medical errors and infrequently offer complete apologies. Although fears about potential litigation are the most commonly cited barrier to apologizing after medical error, the link between litigation risk and the practice of disclosure and apology is tenuous. Other barriers might include the culture of medicine and the inherent psychological difficulties in facing one’s mistakes and apologizing for them. Despite these barriers, incorporating apology into conversations between physicians and patients can address the needs of both parties and can play a role in the effective resolution of disputes related to medical error. PMID:18972177

Bias Errors due to Leakage Effects When Estimating Frequency Response Functions

Directory of Open Access Journals (Sweden)

Andreas Josefsson

2012-01-01

Full Text Available Frequency response functions are often utilized to characterize a system's dynamic response. For a wide range of engineering applications, it is desirable to determine frequency response functions for a system under stochastic excitation. In practice, the measurement data is contaminated by noise and some form of averaging is needed in order to obtain a consistent estimator. With Welch's method, the discrete Fourier transform is used and the data is segmented into smaller blocks so that averaging can be performed when estimating the spectrum. However, this segmentation introduces leakage effects. As a result, the estimated frequency response function suffers from both systematic (bias and random errors due to leakage. In this paper the bias error in the H1 and H2-estimate is studied and a new method is proposed to derive an approximate expression for the relative bias error at the resonance frequency with different window functions. The method is based on using a sum of real exponentials to describe the window's deterministic autocorrelation function. Simple expressions are derived for a rectangular window and a Hanning window. The theoretical expressions are verified with numerical simulations and a very good agreement is found between the results from the proposed bias expressions and the empirical results.

Reducing matrix effect error in EDXRF: Comparative study of using standard and standard less methods for stainless steel samples

International Nuclear Information System (INIS)

Meor Yusoff Meor Sulaiman; Masliana Muhammad; Wilfred, P.

2013-01-01

Even though EDXRF analysis has major advantages in the analysis of stainless steel samples such as simultaneous determination of the minor elements, analysis can be done without sample preparation and non-destructive analysis, the matrix issue arise from the inter element interaction can make the the final quantitative result to be in accurate. The paper relates a comparative quantitative analysis using standard and standard less methods in the determination of these elements. Standard method was done by plotting regression calibration graphs of the interested elements using BCS certified stainless steel standards. Different calibration plots were developed based on the available certified standards and these stainless steel grades include low alloy steel, austenitic, ferritic and high speed. The standard less method on the other hand uses a mathematical modelling with matrix effect correction derived from Lucas-Tooth and Price model. Further improvement on the accuracy of the standard less method was done by inclusion of pure elements into the development of the model. Discrepancy tests were then carried out for these quantitative methods on different certified samples and the results show that the high speed method is most reliable for determining of Ni and the standard less method for Mn. (Author)

An audit strategy for time-to-event outcomes measured with error: application to five randomized controlled trials in oncology.

Science.gov (United States)

Dodd, Lori E; Korn, Edward L; Freidlin, Boris; Gu, Wenjuan; Abrams, Jeffrey S; Bushnell, William D; Canetta, Renzo; Doroshow, James H; Gray, Robert J; Sridhara, Rajeshwari

2013-10-01

Measurement error in time-to-event end points complicates interpretation of treatment effects in clinical trials. Non-differential measurement error is unlikely to produce large bias [1]. When error depends on treatment arm, bias is of greater concern. Blinded-independent central review (BICR) of all images from a trial is commonly undertaken to mitigate differential measurement-error bias that may be present in hazard ratios (HRs) based on local evaluations. Similar BICR and local evaluation HRs may provide reassurance about the treatment effect, but BICR adds considerable time and expense to trials. We describe a BICR audit strategy [2] and apply it to five randomized controlled trials to evaluate its use and to provide practical guidelines. The strategy requires BICR on a subset of study subjects, rather than a complete-case BICR, and makes use of an auxiliary-variable estimator. When the effect size is relatively large, the method provides a substantial reduction in the size of the BICRs. In a trial with 722 participants and a HR of 0.48, an average audit of 28% of the data was needed and always confirmed the treatment effect as assessed by local evaluations. More moderate effect sizes and/or smaller trial sizes required larger proportions of audited images, ranging from 57% to 100% for HRs ranging from 0.55 to 0.77 and sample sizes between 209 and 737. The method is developed for a simple random sample of study subjects. In studies with low event rates, more efficient estimation may result from sampling individuals with events at a higher rate. The proposed strategy can greatly decrease the costs and time associated with BICR, by reducing the number of images undergoing review. The savings will depend on the underlying treatment effect and trial size, with larger treatment effects and larger trials requiring smaller proportions of audited data.

Reliability of different sampling densities for estimating and mapping lichen diversity in biomonitoring studies

International Nuclear Information System (INIS)

Ferretti, M.; Brambilla, E.; Brunialti, G.; Fornasier, F.; Mazzali, C.; Giordani, P.; Nimis, P.L.

2004-01-01

Sampling requirements related to lichen biomonitoring include optimal sampling density for obtaining precise and unbiased estimates of population parameters and maps of known reliability. Two available datasets on a sub-national scale in Italy were used to determine a cost-effective sampling density to be adopted in medium-to-large-scale biomonitoring studies. As expected, the relative error in the mean Lichen Biodiversity (Italian acronym: BL) values and the error associated with the interpolation of BL values for (unmeasured) grid cells increased as the sampling density decreased. However, the increase in size of the error was not linear and even a considerable reduction (up to 50%) in the original sampling effort led to a far smaller increase in errors in the mean estimates (<6%) and in mapping (<18%) as compared with the original sampling densities. A reduction in the sampling effort can result in considerable savings of resources, which can then be used for a more detailed investigation of potentially problematic areas. It is, however, necessary to decide the acceptable level of precision at the design stage of the investigation, so as to select the proper sampling density. - An acceptable level of precision must be decided before determining a sampling design

Learning time-dependent noise to reduce logical errors: real time error rate estimation in quantum error correction

Science.gov (United States)

Huo, Ming-Xia; Li, Ying

2017-12-01

Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error rates. We propose a protocol for monitoring error rates in real time without interrupting the quantum error correction. Any adaptation of the quantum error correction code or its implementation circuit is not required. The protocol can be directly applied to the most advanced quantum error correction techniques, e.g. surface code. A Gaussian processes algorithm is used to estimate and predict error rates based on error correction data in the past. We find that using these estimated error rates, the probability of error correction failures can be significantly reduced by a factor increasing with the code distance.

Voice recognition versus transcriptionist: error rated and productivity in MRI reporting

International Nuclear Information System (INIS)

Strahan, Rodney H.; Schneider-Kolsky, Michal E.

2010-01-01

Full text: Purpose: Despite the frequent introduction of voice recognition (VR) into radiology departments, little evidence still exists about its impact on workflow, error rates and costs. We designed a study to compare typographical errors, turnaround times (TAT) from reported to verified and productivity for VR-generated reports versus transcriptionist-generated reports in MRI. Methods: Fifty MRI reports generated by VR and 50 finalised MRI reports generated by the transcriptionist, of two radiologists, were sampled retrospectively. Two hundred reports were scrutinised for typographical errors and the average TAT from dictated to final approval. To assess productivity, the average MRI reports per hour for one of the radiologists was calculated using data from extra weekend reporting sessions. Results: Forty-two % and 30% of the finalised VR reports for each of the radiologists investigated contained errors. Only 6% and 8% of the transcriptionist-generated reports contained errors. The average TAT for VR was 0 h, and for the transcriptionist reports TAT was 89 and 38.9 h. Productivity was calculated at 8.6 MRI reports per hour using VR and 13.3 MRI reports using the transcriptionist, representing a 55% increase in productivity. Conclusion: Our results demonstrate that VR is not an effective method of generating reports for MRI. Ideally, we would have the report error rate and productivity of a transcriptionist and the TAT of VR.

TEACHING GRAMMAR-IN-CONTEXT AND ITS IMPACT IN MINIMIZING STUDENTS’ GRAMMATICAL ERRORS

Directory of Open Access Journals (Sweden)

Yadhi Nur Amin

2015-11-01

Full Text Available This study is conducted to determine the effectiveness of teaching grammar-in-context to minimize students‘ grammatical errors in writing. The design of the study was a quasi-experimental with a non-randomized pretest-posttest control group. The samples of the study were taken from the population of the tenth-grade students. The control group was taught by conventional grammar which was separately given with writing skills. Likewise, the experimental one was treated by teaching grammar-in-context. The results of the study showed that the mean score in the post-test was higher than that in the pretest; and the mean score of experimental group increased 16.20 point after the treatment. This result indicated that teaching grammarin-context is considered to be effective in minimizing students‘ grammatical errors in writing.

Margin of Valuation Error Among Nigerian Valuers: Postulating an ...

African Journals Online (AJOL)

Study on margin of error aims at capturing the response of Nigerian valuers and their clients from the financial sector to their permissable margin of error with a view to establishing the bracket outside which the valuer is considered incompetent. The opinion of 300 Estate Surveyors and Valuers were sampled using simple ...

Students' errors in solving linear equation word problems: Case ...

African Journals Online (AJOL)

The study examined errors students make in solving linear equation word problems with a view to expose the nature of these errors and to make suggestions for classroom teaching. A diagnostic test comprising 10 linear equation word problems, was administered to a sample (n=130) of senior high school first year Home ...

Quantification of the effects of dependence on human error probabilities

International Nuclear Information System (INIS)

Bell, B.J.; Swain, A.D.

1980-01-01

In estimating the probabilities of human error in the performance of a series of tasks in a nuclear power plant, the situation-specific characteristics of the series must be considered. A critical factor not to be overlooked in this estimation is the dependence or independence that pertains to any of the several pairs of task performances. In discussing the quantification of the effects of dependence, the event tree symbology described will be used. In any series of tasks, the only dependence considered for quantification in this document will be that existing between the task of interest and the immediately preceeding task. Tasks performed earlier in the series may have some effect on the end task, but this effect is considered negligible

Burnout is associated with changes in error and feedback processing.

Science.gov (United States)

Gajewski, Patrick D; Boden, Sylvia; Freude, Gabriele; Potter, Guy G; Falkenstein, Michael

2017-10-01

Burnout is a pattern of complaints in individuals with emotionally demanding jobs that is often seen as a precursor of depression. One often reported symptom of burnout is cognitive decline. To analyze cognitive control and to differentiate between subclinical burnout and mild to moderate depression a double-blinded study was conducted that investigates changes in the processing of performance errors and feedback in a task switching paradigm. Fifty-one of 76 employees from emotionally demanding jobs showed a sufficient number of errors to be included in the analysis. The sample was subdivided into groups with low (EE-) and high (EE+) emotional exhaustion and no (DE-) and mild to moderate depression (DE+). The behavioral data did not significantly differ between the groups. In contrast, in the EE+ group, the error negativity (Ne/ERN) was enhanced while the error positivity (Pe) did not differ between the EE+ and EE- groups. After negative feedback the feedback-related negativity (FRN) was enhanced, while the subsequent positivity (FRP) was reduced in EE+ relative to EE-. None of these effects were observed in the DE+ vs. DE-. These results suggest an upregulation of error and negative feedback processing, while the later processing of negative feedback was attenuated in employees with subclinical burnout but not in mild to moderate depression. Copyright © 2017 Elsevier B.V. All rights reserved.

Medication errors: prescribing faults and prescription errors.

Science.gov (United States)

Velo, Giampaolo P; Minuz, Pietro

2009-06-01

1. Medication errors are common in general practice and in hospitals. Both errors in the act of writing (prescription errors) and prescribing faults due to erroneous medical decisions can result in harm to patients. 2. Any step in the prescribing process can generate errors. Slips, lapses, or mistakes are sources of errors, as in unintended omissions in the transcription of drugs. Faults in dose selection, omitted transcription, and poor handwriting are common. 3. Inadequate knowledge or competence and incomplete information about clinical characteristics and previous treatment of individual patients can result in prescribing faults, including the use of potentially inappropriate medications. 4. An unsafe working environment, complex or undefined procedures, and inadequate communication among health-care personnel, particularly between doctors and nurses, have been identified as important underlying factors that contribute to prescription errors and prescribing faults. 5. Active interventions aimed at reducing prescription errors and prescribing faults are strongly recommended. These should be focused on the education and training of prescribers and the use of on-line aids. The complexity of the prescribing procedure should be reduced by introducing automated systems or uniform prescribing charts, in order to avoid transcription and omission errors. Feedback control systems and immediate review of prescriptions, which can be performed with the assistance of a hospital pharmacist, are also helpful. Audits should be performed periodically.

Theoretical-and experimental analysis of the errors involved in the wood moisture determination by gamma-ray attenuation

International Nuclear Information System (INIS)

Aguiar, O.

1983-01-01

The sources of errors in wood moisture determination by gamma-ray attenuation were sought. Equations were proposed for determining errors and for ideal sample thickness. A series of measurements of moisture content in wood samples of Pinus oocarpa was made and the experimental errors were compared with the theoretical errors. (Author) [pt

An Agent-Based Intervention to Assist Drivers Under Stereotype Threat: Effects of In-Vehicle Agents' Attributional Error Feedback.

Science.gov (United States)

Joo, Yeon Kyoung; Lee-Won, Roselyn J

2016-10-01

For members of a group negatively stereotyped in a domain, making mistakes can aggravate the influence of stereotype threat because negative stereotypes often blame target individuals and attribute the outcome to their lack of ability. Virtual agents offering real-time error feedback may influence performance under stereotype threat by shaping the performers' attributional perception of errors they commit. We explored this possibility with female drivers, considering the prevalence of the "women-are-bad-drivers" stereotype. Specifically, we investigated how in-vehicle voice agents offering error feedback based on responsibility attribution (internal vs. external) and outcome attribution (ability vs. effort) influence female drivers' performance under stereotype threat. In addressing this question, we conducted an experiment in a virtual driving simulation environment that provided moment-to-moment error feedback messages. Participants performed a challenging driving task and made mistakes preprogrammed to occur. Results showed that the agent's error feedback with outcome attribution moderated the stereotype threat effect on driving performance. Participants under stereotype threat had a smaller number of collisions when the errors were attributed to effort than to ability. In addition, outcome attribution feedback moderated the effect of responsibility attribution on driving performance. Implications of these findings are discussed.

How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?

Directory of Open Access Journals (Sweden)

Brady T West

Full Text Available Secondary analyses of survey data collected from large probability samples of persons or establishments further scientific progress in many fields. The complex design features of these samples improve data collection efficiency, but also require analysts to account for these features when conducting analysis. Unfortunately, many secondary analysts from fields outside of statistics, biostatistics, and survey methodology do not have adequate training in this area, and as a result may apply incorrect statistical methods when analyzing these survey data sets. This in turn could lead to the publication of incorrect inferences based on the survey data that effectively negate the resources dedicated to these surveys. In this article, we build on the results of a preliminary meta-analysis of 100 peer-reviewed journal articles presenting analyses of data from a variety of national health surveys, which suggested that analytic errors may be extremely prevalent in these types of investigations. We first perform a meta-analysis of a stratified random sample of 145 additional research products analyzing survey data from the Scientists and Engineers Statistical Data System (SESTAT, which describes features of the U.S. Science and Engineering workforce, and examine trends in the prevalence of analytic error across the decades used to stratify the sample. We once again find that analytic errors appear to be quite prevalent in these studies. Next, we present several example analyses of real SESTAT data, and demonstrate that a failure to perform these analyses correctly can result in substantially biased estimates with standard errors that do not adequately reflect complex sample design features. Collectively, the results of this investigation suggest that reviewers of this type of research need to pay much closer attention to the analytic methods employed by researchers attempting to publish or present secondary analyses of survey data.

How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?

Science.gov (United States)

West, Brady T.; Sakshaug, Joseph W.; Aurelien, Guy Alain S.

2016-01-01

Secondary analyses of survey data collected from large probability samples of persons or establishments further scientific progress in many fields. The complex design features of these samples improve data collection efficiency, but also require analysts to account for these features when conducting analysis. Unfortunately, many secondary analysts from fields outside of statistics, biostatistics, and survey methodology do not have adequate training in this area, and as a result may apply incorrect statistical methods when analyzing these survey data sets. This in turn could lead to the publication of incorrect inferences based on the survey data that effectively negate the resources dedicated to these surveys. In this article, we build on the results of a preliminary meta-analysis of 100 peer-reviewed journal articles presenting analyses of data from a variety of national health surveys, which suggested that analytic errors may be extremely prevalent in these types of investigations. We first perform a meta-analysis of a stratified random sample of 145 additional research products analyzing survey data from the Scientists and Engineers Statistical Data System (SESTAT), which describes features of the U.S. Science and Engineering workforce, and examine trends in the prevalence of analytic error across the decades used to stratify the sample. We once again find that analytic errors appear to be quite prevalent in these studies. Next, we present several example analyses of real SESTAT data, and demonstrate that a failure to perform these analyses correctly can result in substantially biased estimates with standard errors that do not adequately reflect complex sample design features. Collectively, the results of this investigation suggest that reviewers of this type of research need to pay much closer attention to the analytic methods employed by researchers attempting to publish or present secondary analyses of survey data. PMID:27355817

The influence of different error estimates in the detection of postoperative cognitive dysfunction using reliable change indices with correction for practice effects.

Science.gov (United States)

Lewis, Matthew S; Maruff, Paul; Silbert, Brendan S; Evered, Lis A; Scott, David A

2007-02-01

The reliable change index (RCI) expresses change relative to its associated error, and is useful in the identification of postoperative cognitive dysfunction (POCD). This paper examines four common RCIs that each account for error in different ways. Three rules incorporate a constant correction for practice effects and are contrasted with the standard RCI that had no correction for practice. These rules are applied to 160 patients undergoing coronary artery bypass graft (CABG) surgery who completed neuropsychological assessments preoperatively and 1 week postoperatively using error and reliability data from a comparable healthy nonsurgical control group. The rules all identify POCD in a similar proportion of patients, but the use of the within-subject standard deviation (WSD), expressing the effects of random error, as an error estimate is a theoretically appropriate denominator when a constant error correction, removing the effects of systematic error, is deducted from the numerator in a RCI.

Understanding human management of automation errors

Science.gov (United States)

McBride, Sara E.; Rogers, Wendy A.; Fisk, Arthur D.

2013-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance. PMID:25383042

Sampling or gambling

Energy Technology Data Exchange (ETDEWEB)

Gy, P.M.

1981-12-01

Sampling can be compared to no other technique. A mechanical sampler must above all be selected according to its aptitude for supressing or reducing all components of the sampling error. Sampling is said to be correct when it gives all elements making up the batch of matter submitted to sampling an uniform probability of being selected. A sampler must be correctly designed, built, installed, operated and maintained. When the conditions of sampling correctness are not strictly respected, the sampling error can no longer be controlled and can, unknown to the user, be unacceptably large: the sample is no longer representative. The implementation of an incorrect sampler is a form of gambling and this paper intends to show that at this game the user is nearly always the loser in the long run. The users' and the manufacturers' interests may diverge and the standards which should safeguard the users' interests very often fail to do so by tolerating or even recommending incorrect techniques such as the implementation of too narrow cutters traveling too fast through the stream to be sampled.

Radon measurements-discussion of error estimates for selected methods

International Nuclear Information System (INIS)

Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav

2010-01-01

The main sources of uncertainties for grab sampling, short-term (charcoal canisters) and long term (track detectors) measurements are: systematic bias of reference equipment; random Poisson and non-Poisson errors during calibration; random Poisson and non-Poisson errors during measurements. The origins of non-Poisson random errors during calibration are different for different kinds of instrumental measurements. The main sources of uncertainties for retrospective measurements conducted by surface traps techniques can be divided in two groups: errors of surface 210 Pb ( 210 Po) activity measurements and uncertainties of transfer from 210 Pb surface activity in glass objects to average radon concentration during this object exposure. It's shown that total measurement error of surface trap retrospective technique can be decreased to 35%.

Investigating Medication Errors in Educational Health Centers of Kermanshah

Directory of Open Access Journals (Sweden)

Mohsen Mohammadi

2015-08-01

Full Text Available Background and objectives : Medication errors can be a threat to the safety of patients. Preventing medication errors requires reporting and investigating such errors. The present study was conducted with the purpose of investigating medication errors in educational health centers of Kermanshah. Material and Methods: The present research is an applied, descriptive-analytical study and is done as a survey. Error Report of Ministry of Health and Medical Education was used for data collection. The population of the study included all the personnel (nurses, doctors, paramedics of educational health centers of Kermanshah. Among them, those who reported the committed errors were selected as the sample of the study. The data analysis was done using descriptive statistics and Chi 2 Test using SPSS version 18. Results: The findings of the study showed that most errors were related to not using medication properly, the least number of errors were related to improper dose, and the majority of errors occurred in the morning. The most frequent reason for errors was staff negligence and the least frequent was the lack of knowledge. Conclusion: The health care system should create an environment for detecting and reporting errors by the personnel, recognizing related factors causing errors, training the personnel and create a good working environment and standard workload.

Eliminating US hospital medical errors.

Science.gov (United States)

Kumar, Sameer; Steinebach, Marc

2008-01-01

Healthcare costs in the USA have continued to rise steadily since the 1980s. Medical errors are one of the major causes of deaths and injuries of thousands of patients every year, contributing to soaring healthcare costs. The purpose of this study is to examine what has been done to deal with the medical-error problem in the last two decades and present a closed-loop mistake-proof operation system for surgery processes that would likely eliminate preventable medical errors. The design method used is a combination of creating a service blueprint, implementing the six sigma DMAIC cycle, developing cause-and-effect diagrams as well as devising poka-yokes in order to develop a robust surgery operation process for a typical US hospital. In the improve phase of the six sigma DMAIC cycle, a number of poka-yoke techniques are introduced to prevent typical medical errors (identified through cause-and-effect diagrams) that may occur in surgery operation processes in US hospitals. It is the authors' assertion that implementing the new service blueprint along with the poka-yokes, will likely result in the current medical error rate to significantly improve to the six-sigma level. Additionally, designing as many redundancies as possible in the delivery of care will help reduce medical errors. Primary healthcare providers should strongly consider investing in adequate doctor and nurse staffing, and improving their education related to the quality of service delivery to minimize clinical errors. This will lead to an increase in higher fixed costs, especially in the shorter time frame. This paper focuses additional attention needed to make a sound technical and business case for implementing six sigma tools to eliminate medical errors that will enable hospital managers to increase their hospital's profitability in the long run and also ensure patient safety.

Refractive Errors in State Junior High School Students in Bandung

Directory of Open Access Journals (Sweden)

Sabila Tasyakur Nikmah

2016-12-01

Full Text Available Background: Uncorrected refractive error is one of the avoidable causes of vision impairment in children and adults. Vision problem in children has been shown to affect their psychological and academic performance. This study aims at identifying and gaining more insights on the characteristic of the refractive errors in state junior high school students in Bandung to avoid uncorrected refractive errors. Methods: A cross-sectional study was conducted in September–November 2015 in state junior high schools in Bandung, West Java, Indonesia. Sample was selected using multistage random sampling technique. Children were examined using tumbling E examination; then students with visual acuity worse than 6/12 underwent Snellen Chart test, refractometry without pupil dilatation, correction with trial lens, then was followed by direct ophthalmoscopy. Results: From a total of 435 children who completed all the examination, 80 children (18.39% had refractive errors; consisted of 151 eyes (94.38% with myopia and 9 eyes (5.62% with astigmatism. Refractive errors were found to be more common in female children (73.7% than male children (26.3%. Among those with refractive errors, 45 children (56.3% did not use any corrective glasses before the examination. Conclusions: Routine refractive error test in vision screening examination is needed for students. It is equally important to raise more awareness toward eye disease in community.

The Effect of Error Correlation on Interfactor Correlation in Psychometric Measurement

Science.gov (United States)

Westfall, Peter H.; Henning, Kevin S. S.; Howell, Roy D.

2012-01-01

This article shows how interfactor correlation is affected by error correlations. Theoretical and practical justifications for error correlations are given, and a new equivalence class of models is presented to explain the relationship between interfactor correlation and error correlations. The class allows simple, parsimonious modeling of error…

Robust Least-Squares Support Vector Machine With Minimization of Mean and Variance of Modeling Error.

Science.gov (United States)

Lu, Xinjiang; Liu, Wenbo; Zhou, Chuang; Huang, Minghui

2017-06-13

The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers. In this paper, a robust LS-SVM method is proposed and is shown to have more reliable performance when modeling a nonlinear system under conditions where Gaussian or non-Gaussian noise is present. The construction of a new objective function allows for a reduction of the mean of the modeling error as well as the minimization of its variance, and it does not constrain the mean of the modeling error to zero. This differs from the traditional LS-SVM, which uses a worst-case scenario approach in order to minimize the modeling error and constrains the mean of the modeling error to zero. In doing so, the proposed method takes the modeling error distribution information into consideration and is thus less conservative and more robust in regards to random noise. A solving method is then developed in order to determine the optimal parameters for the proposed robust LS-SVM. An additional analysis indicates that the proposed LS-SVM gives a smaller weight to a large-error training sample and a larger weight to a small-error training sample, and is thus more robust than the traditional LS-SVM. The effectiveness of the proposed robust LS-SVM is demonstrated using both artificial and real life cases.

Selection of anchor values for human error probability estimation

International Nuclear Information System (INIS)

Buffardi, L.C.; Fleishman, E.A.; Allen, J.A.

1989-01-01

There is a need for more dependable information to assist in the prediction of human errors in nuclear power environments. The major objective of the current project is to establish guidelines for using error probabilities from other task settings to estimate errors in the nuclear environment. This involves: (1) identifying critical nuclear tasks, (2) discovering similar tasks in non-nuclear environments, (3) finding error data for non-nuclear tasks, and (4) establishing error-rate values for the nuclear tasks based on the non-nuclear data. A key feature is the application of a classification system to nuclear and non-nuclear tasks to evaluate their similarities and differences in order to provide a basis for generalizing human error estimates across tasks. During the first eight months of the project, several classification systems have been applied to a sample of nuclear tasks. They are discussed in terms of their potential for establishing task equivalence and transferability of human error rates across situations

Design of an error-free nondestructive plutonium assay facility

International Nuclear Information System (INIS)

Moore, C.B.; Steward, W.E.

1987-01-01

An automated, at-line nondestructive assay (NDA) laboratory is installed in facilities recently constructed at the Savannah River Plant. The laboratory will enhance nuclear materials accounting in new plutonium scrap and waste recovery facilities. The advantages of at-line NDA operations will not be realized if results are clouded by errors in analytical procedures, sample identification, record keeping, or techniques for extracting samples from process streams. Minimization of such errors has been a primary design objective for the new facility. Concepts for achieving that objective include mechanizing the administrative tasks of scheduling activities in the laboratory, identifying samples, recording and storing assay data, and transmitting results information to process control and materials accounting functions. These concepts have been implemented in an analytical computer system that is programmed to avoid the obvious sources of error encountered in laboratory operations. The laboratory computer exchanges information with process control and materials accounting computers, transmitting results information and obtaining process data and accounting information as required to guide process operations and maintain current records of materials flow through the new facility

Barriers to medical error reporting

Directory of Open Access Journals (Sweden)

Jalal Poorolajal

2015-01-01

Full Text Available Background: This study was conducted to explore the prevalence of medical error underreporting and associated barriers. Methods: This cross-sectional study was performed from September to December 2012. Five hospitals, affiliated with Hamadan University of Medical Sciences, in Hamedan,Iran were investigated. A self-administered questionnaire was used for data collection. Participants consisted of physicians, nurses, midwives, residents, interns, and staffs of radiology and laboratory departments. Results: Overall, 50.26% of subjects had committed but not reported medical errors. The main reasons mentioned for underreporting were lack of effective medical error reporting system (60.0%, lack of proper reporting form (51.8%, lack of peer supporting a person who has committed an error (56.0%, and lack of personal attention to the importance of medical errors (62.9%. The rate of committing medical errors was higher in men (71.4%, age of 50-40 years (67.6%, less-experienced personnel (58.7%, educational level of MSc (87.5%, and staff of radiology department (88.9%. Conclusions: This study outlined the main barriers to reporting medical errors and associated factors that may be helpful for healthcare organizations in improving medical error reporting as an essential component for patient safety enhancement.

The effect of TWD estimation error on the geometry of machined surfaces in micro-EDM milling

DEFF Research Database (Denmark)

Puthumana, Govindan; Bissacco, Giuliano; Hansen, Hans Nørgaard

In micro EDM (electrical discharge machining) milling, tool electrode wear must be effectively compensated in order to achieve high accuracy of machined features [1]. Tool wear compensation in micro-EDM milling can be based on off-line techniques with limited accuracy such as estimation...... and statistical characterization of the discharge population [3]. The TWD based approach permits the direct control of the position of the tool electrode front surface. However, TWD estimation errors will generate a self-amplifying error on the tool electrode axial depth during micro-EDM milling. Therefore....... The error propagation effect is demonstrated through a software simulation tool developed by the authors for determination of the correct TWD for subsequent use in compensation of electrode wear in EDM milling. The implemented model uses an initial arbitrary estimation of TWD and a single experiment...

Accounting for optical errors in microtensiometry.

Science.gov (United States)

Hinton, Zachary R; Alvarez, Nicolas J

2018-09-15

Drop shape analysis (DSA) techniques measure interfacial tension subject to error in image analysis and the optical system. While considerable efforts have been made to minimize image analysis errors, very little work has treated optical errors. There are two main sources of error when considering the optical system: the angle of misalignment and the choice of focal plane. Due to the convoluted nature of these sources, small angles of misalignment can lead to large errors in measured curvature. We demonstrate using microtensiometry the contributions of these sources to measured errors in radius, and, more importantly, deconvolute the effects of misalignment and focal plane. Our findings are expected to have broad implications on all optical techniques measuring interfacial curvature. A geometric model is developed to analytically determine the contributions of misalignment angle and choice of focal plane on measurement error for spherical cap interfaces. This work utilizes a microtensiometer to validate the geometric model and to quantify the effect of both sources of error. For the case of a microtensiometer, an empirical calibration is demonstrated that corrects for optical errors and drastically simplifies implementation. The combination of geometric modeling and experimental results reveal a convoluted relationship between the true and measured interfacial radius as a function of the misalignment angle and choice of focal plane. The validated geometric model produces a full operating window that is strongly dependent on the capillary radius and spherical cap height. In all cases, the contribution of optical errors is minimized when the height of the spherical cap is equivalent to the capillary radius, i.e. a hemispherical interface. The understanding of these errors allow for correct measure of interfacial curvature and interfacial tension regardless of experimental setup. For the case of microtensiometry, this greatly decreases the time for experimental setup

A Study of Trial and Error Learning in Technology, Engineering, and Design Education

Science.gov (United States)

Franzen, Marissa Marie Sloan

2016-01-01

The purpose of this research study was to determine if trial and error learning was an effective, practical, and efficient learning method for Technology, Engineering, and Design Education students at the post-secondary level. A mixed methods explanatory research design was used to measure the viability of the learning source. The study sample was…

Determining the sample size for co-dominant molecular marker-assisted linkage detection for a monogenic qualitative trait by controlling the type-I and type-II errors in a segregating F2 population.

Science.gov (United States)

Hühn, M; Piepho, H P

2003-03-01

Tests for linkage are usually performed using the lod score method. A critical question in linkage analyses is the choice of sample size. The appropriate sample size depends on the desired type-I error and power of the test. This paper investigates the exact type-I error and power of the lod score method in a segregating F(2) population with co-dominant markers and a qualitative monogenic dominant-recessive trait. For illustration, a disease-resistance trait is considered, where the susceptible allele is recessive. A procedure is suggested for finding the appropriate sample size. It is shown that recessive plants have about twice the information content of dominant plants, so the former should be preferred for linkage detection. In some cases the exact alpha-values for a given nominal alpha may be rather small due to the discrete nature of the sampling distribution in small samples. We show that a gain in power is possible by using exact methods.

Effect of Pointing Error on the BER Performance of an Optical CDMA FSO Link with SIK Receiver

Science.gov (United States)

Nazrul Islam, A. K. M.; Majumder, S. P.

2017-12-01

An analytical approach is presented for an optical code division multiple access (OCDMA) system over free space optical (FSO) channel considering the effect of pointing error between the transmitter and the receiver. Analysis is carried out with an optical sequence inverse keying (SIK) correlator receiver with intensity modulation and direct detection (IM/DD) to find the bit error rate (BER) with pointing error. The results are evaluated numerically in terms of signal-to-noise plus multi-access interference (MAI) ratio, BER and power penalty due to pointing error. It is noticed that the OCDMA FSO system is highly affected by pointing error with significant power penalty at a BER of 10-6 and 10-9. For example, penalty at BER 10-9 is found to be 9 dB corresponding to normalized pointing error of 1.4 for 16 users with processing gain of 256 and is reduced to 6.9 dB when the processing gain is increased to 1,024.

Students’ Errors in Geometry Viewed from Spatial Intelligence

Science.gov (United States)

Riastuti, N.; Mardiyana, M.; Pramudya, I.

2017-09-01

Geometry is one of the difficult materials because students must have ability to visualize, describe images, draw shapes, and know the kind of shapes. This study aim is to describe student error based on Newmans’ Error Analysis in solving geometry problems viewed from spatial intelligence. This research uses descriptive qualitative method by using purposive sampling technique. The datas in this research are the result of geometri material test and interview by the 8th graders of Junior High School in Indonesia. The results of this study show that in each category of spatial intelligence has a different type of error in solving the problem on the material geometry. Errors are mostly made by students with low spatial intelligence because they have deficiencies in visual abilities. Analysis of student error viewed from spatial intelligence is expected to help students do reflection in solving the problem of geometry.

Analyzing the errors of DFT approximations for compressed water systems

International Nuclear Information System (INIS)

Alfè, D.; Bartók, A. P.; Csányi, G.; Gillan, M. J.

2014-01-01

We report an extensive study of the errors of density functional theory (DFT) approximations for compressed water systems. The approximations studied are based on the widely used PBE and BLYP exchange-correlation functionals, and we characterize their errors before and after correction for 1- and 2-body errors, the corrections being performed using the methods of Gaussian approximation potentials. The errors of the uncorrected and corrected approximations are investigated for two related types of water system: first, the compressed liquid at temperature 420 K and density 1.245 g/cm 3 where the experimental pressure is 15 kilobars; second, thermal samples of compressed water clusters from the trimer to the 27-mer. For the liquid, we report four first-principles molecular dynamics simulations, two generated with the uncorrected PBE and BLYP approximations and a further two with their 1- and 2-body corrected counterparts. The errors of the simulations are characterized by comparing with experimental data for the pressure, with neutron-diffraction data for the three radial distribution functions, and with quantum Monte Carlo (QMC) benchmarks for the energies of sets of configurations of the liquid in periodic boundary conditions. The DFT errors of the configuration samples of compressed water clusters are computed using QMC benchmarks. We find that the 2-body and beyond-2-body errors in the liquid are closely related to similar errors exhibited by the clusters. For both the liquid and the clusters, beyond-2-body errors of DFT make a substantial contribution to the overall errors, so that correction for 1- and 2-body errors does not suffice to give a satisfactory description. For BLYP, a recent representation of 3-body energies due to Medders, Babin, and Paesani [J. Chem. Theory Comput. 9, 1103 (2013)] gives a reasonably good way of correcting for beyond-2-body errors, after which the remaining errors are typically 0.5 mE h ≃ 15 meV/monomer for the liquid and the

Reduced error signalling in medication-naive children with ADHD

DEFF Research Database (Denmark)

Plessen, Kerstin J; Allen, Elena A; Eichele, Heike

2016-01-01

reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN. LIMITATIONS: Our study was limited by the modest sample size......BACKGROUND: We examined the blood-oxygen level-dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: We acquired...

Testing and Inference in Nonlinear Cointegrating Vector Error Correction Models

DEFF Research Database (Denmark)

Kristensen, Dennis; Rahbæk, Anders

In this paper, we consider a general class of vector error correction models which allow for asymmetric and non-linear error correction. We provide asymptotic results for (quasi-)maximum likelihood (QML) based estimators and tests. General hypothesis testing is considered, where testing...... of non-stationary non-linear time series models. Thus the paper provides a full asymptotic theory for estimators as well as standard and non-standard test statistics. The derived asymptotic results prove to be new compared to results found elsewhere in the literature due to the impact of the estimated...... symmetric non-linear error correction considered. A simulation study shows that the fi…nite sample properties of the bootstrapped tests are satisfactory with good size and power properties for reasonable sample sizes....

Testing and Inference in Nonlinear Cointegrating Vector Error Correction Models

DEFF Research Database (Denmark)

Kristensen, Dennis; Rahbek, Anders

In this paper, we consider a general class of vector error correction models which allow for asymmetric and non-linear error correction. We provide asymptotic results for (quasi-)maximum likelihood (QML) based estimators and tests. General hypothesis testing is considered, where testing...... of non-stationary non-linear time series models. Thus the paper provides a full asymptotic theory for estimators as well as standard and non-standard test statistics. The derived asymptotic results prove to be new compared to results found elsewhere in the literature due to the impact of the estimated...... symmetric non-linear error correction are considered. A simulation study shows that the finite sample properties of the bootstrapped tests are satisfactory with good size and power properties for reasonable sample sizes....

Comparing Absolute Error with Squared Error for Evaluating Empirical Models of Continuous Variables: Compositions, Implications, and Consequences

Science.gov (United States)

Gao, J.

2014-12-01

Reducing modeling error is often a major concern of empirical geophysical models. However, modeling errors can be defined in different ways: When the response variable is continuous, the most commonly used metrics are squared (SQ) and absolute (ABS) errors. For most applications, ABS error is the more natural, but SQ error is mathematically more tractable, so is often used as a substitute with little scientific justification. Existing literature has not thoroughly investigated the implications of using SQ error in place of ABS error, especially not geospatially. This study compares the two metrics through the lens of bias-variance decomposition (BVD). BVD breaks down the expected modeling error of each model evaluation point into bias (systematic error), variance (model sensitivity), and noise (observation instability). It offers a way to probe the composition of various error metrics. I analytically derived the BVD of ABS error and compared it with the well-known SQ error BVD, and found that not only the two metrics measure the characteristics of the probability distributions of modeling errors differently, but also the effects of these characteristics on the overall expected error are different. Most notably, under SQ error all bias, variance, and noise increase expected error, while under ABS error certain parts of the error components reduce expected error. Since manipulating these subtractive terms is a legitimate way to reduce expected modeling error, SQ error can never capture the complete story embedded in ABS error. I then empirically compared the two metrics with a supervised remote sensing model for mapping surface imperviousness. Pair-wise spatially-explicit comparison for each error component showed that SQ error overstates all error components in comparison to ABS error, especially variance-related terms. Hence, substituting ABS error with SQ error makes model performance appear worse than it actually is, and the analyst would more likely accept a

Effective connectivity of visual word recognition and homophone orthographic errors

Science.gov (United States)

Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel; Zarabozo-Hurtado, Daniel; González-Garrido, Andrés A.; Gudayol-Ferré, Esteve

2015-01-01

The study of orthographic errors in a transparent language like Spanish is an important topic in relation to writing acquisition. The development of neuroimaging techniques, particularly functional magnetic resonance imaging (fMRI), has enabled the study of such relationships between brain areas. The main objective of the present study was to explore the patterns of effective connectivity by processing pseudohomophone orthographic errors among subjects with high and low spelling skills. Two groups of 12 Mexican subjects each, matched by age, were formed based on their results in a series of ad hoc spelling-related out-scanner tests: a high spelling skills (HSSs) group and a low spelling skills (LSSs) group. During the f MRI session, two experimental tasks were applied (spelling recognition task and visuoperceptual recognition task). Regions of Interest and their signal values were obtained for both tasks. Based on these values, structural equation models (SEMs) were obtained for each group of spelling competence (HSS and LSS) and task through maximum likelihood estimation, and the model with the best fit was chosen in each case. Likewise, dynamic causal models (DCMs) were estimated for all the conditions across tasks and groups. The HSS group’s SEM results suggest that, in the spelling recognition task, the right middle temporal gyrus, and, to a lesser extent, the left parahippocampal gyrus receive most of the significant effects, whereas the DCM results in the visuoperceptual recognition task show less complex effects, but still congruent with the previous results, with an important role in several areas. In general, these results are consistent with the major findings in partial studies about linguistic activities but they are the first analyses of statistical effective brain connectivity in transparent languages. PMID:26042070

The Effect of an Electronic Checklist on Critical Care Provider Workload, Errors, and Performance.

Science.gov (United States)

Thongprayoon, Charat; Harrison, Andrew M; O'Horo, John C; Berrios, Ronaldo A Sevilla; Pickering, Brian W; Herasevich, Vitaly

2016-03-01

The strategy used to improve effective checklist use in intensive care unit (ICU) setting is essential for checklist success. This study aimed to test the hypothesis that an electronic checklist could reduce ICU provider workload, errors, and time to checklist completion, as compared to a paper checklist. This was a simulation-based study conducted at an academic tertiary hospital. All participants completed checklists for 6 ICU patients: 3 using an electronic checklist and 3 using an identical paper checklist. In both scenarios, participants had full access to the existing electronic medical record system. The outcomes measured were workload (defined using the National Aeronautics and Space Association task load index [NASA-TLX]), the number of checklist errors, and time to checklist completion. Two independent clinician reviewers, blinded to participant results, served as the reference standard for checklist error calculation. Twenty-one ICU providers participated in this study. This resulted in the generation of 63 simulated electronic checklists and 63 simulated paper checklists. The median NASA-TLX score was 39 for the electronic checklist and 50 for the paper checklist (P = .005). The median number of checklist errors for the electronic checklist was 5, while the median number of checklist errors for the paper checklist was 8 (P = .003). The time to checklist completion was not significantly different between the 2 checklist formats (P = .76). The electronic checklist significantly reduced provider workload and errors without any measurable difference in the amount of time required for checklist completion. This demonstrates that electronic checklists are feasible and desirable in the ICU setting. © The Author(s) 2014.

Reliability and error analysis on xenon/CT CBF

International Nuclear Information System (INIS)

Zhang, Z.

2000-01-01

This article provides a quantitative error analysis of a simulation model of xenon/CT CBF in order to investigate the behavior and effect of different types of errors such as CT noise, motion artifacts, lower percentage of xenon supply, lower tissue enhancements, etc. A mathematical model is built to simulate these errors. By adjusting the initial parameters of the simulation model, we can scale the Gaussian noise, control the percentage of xenon supply, and change the tissue enhancement with different kVp settings. The motion artifact will be treated separately by geometrically shifting the sequential CT images. The input function is chosen from an end-tidal xenon curve of a practical study. Four kinds of cerebral blood flow, 10, 20, 50, and 80 cc/100 g/min, are examined under different error environments and the corresponding CT images are generated following the currently popular timing protocol. The simulated studies will be fed to a regular xenon/CT CBF system for calculation and evaluation. A quantitative comparison is given to reveal the behavior and effect of individual error resources. Mixed error testing is also provided to inspect the combination effect of errors. The experiment shows that CT noise is still a major error resource. The motion artifact affects the CBF results more geometrically than quantitatively. Lower xenon supply has a lesser effect on the results, but will reduce the signal/noise ratio. The lower xenon enhancement will lower the flow values in all areas of brain. (author)

Cognitive aspect of diagnostic errors.

Science.gov (United States)

Phua, Dong Haur; Tan, Nigel C K

2013-01-01

Diagnostic errors can result in tangible harm to patients. Despite our advances in medicine, the mental processes required to make a diagnosis exhibits shortcomings, causing diagnostic errors. Cognitive factors are found to be an important cause of diagnostic errors. With new understanding from psychology and social sciences, clinical medicine is now beginning to appreciate that our clinical reasoning can take the form of analytical reasoning or heuristics. Different factors like cognitive biases and affective influences can also impel unwary clinicians to make diagnostic errors. Various strategies have been proposed to reduce the effect of cognitive biases and affective influences when clinicians make diagnoses; however evidence for the efficacy of these methods is still sparse. This paper aims to introduce the reader to the cognitive aspect of diagnostic errors, in the hope that clinicians can use this knowledge to improve diagnostic accuracy and patient outcomes.

EFFECT OF MEASUREMENT ERRORS ON PREDICTED COSMOLOGICAL CONSTRAINTS FROM SHEAR PEAK STATISTICS WITH LARGE SYNOPTIC SURVEY TELESCOPE

Energy Technology Data Exchange (ETDEWEB)

Bard, D.; Chang, C.; Kahn, S. M.; Gilmore, K.; Marshall, S. [KIPAC, Stanford University, 452 Lomita Mall, Stanford, CA 94309 (United States); Kratochvil, J. M.; Huffenberger, K. M. [Department of Physics, University of Miami, Coral Gables, FL 33124 (United States); May, M. [Physics Department, Brookhaven National Laboratory, Upton, NY 11973 (United States); AlSayyad, Y.; Connolly, A.; Gibson, R. R.; Jones, L.; Krughoff, S. [Department of Astronomy, University of Washington, Seattle, WA 98195 (United States); Ahmad, Z.; Bankert, J.; Grace, E.; Hannel, M.; Lorenz, S. [Department of Physics, Purdue University, West Lafayette, IN 47907 (United States); Haiman, Z.; Jernigan, J. G., E-mail: djbard@slac.stanford.edu [Department of Astronomy and Astrophysics, Columbia University, New York, NY 10027 (United States); and others

2013-09-01

We study the effect of galaxy shape measurement errors on predicted cosmological constraints from the statistics of shear peak counts with the Large Synoptic Survey Telescope (LSST). We use the LSST Image Simulator in combination with cosmological N-body simulations to model realistic shear maps for different cosmological models. We include both galaxy shape noise and, for the first time, measurement errors on galaxy shapes. We find that the measurement errors considered have relatively little impact on the constraining power of shear peak counts for LSST.

Error orientation questionnaire (EOQ): reliability, validity, and different language equivalence

NARCIS (Netherlands)

Rybowiak, V.; Garst, H.; Frese, M.; Batinic, B.

1999-01-01

An Error Orientation Questionnaire (EOQ) was developed, consisting of eight scales on attitudes to and on coping with errors at work. In Study I (representative sample of a German city, N=478) six scales were developed with the help of a confirmatory factor analysis using LISREL techniques. They

Errors in Neonatology

Directory of Open Access Journals (Sweden)

Antonio Boldrini

2013-06-01

Full Text Available Introduction: Danger and errors are inherent in human activities. In medical practice errors can lean to adverse events for patients. Mass media echo the whole scenario. Methods: We reviewed recent published papers in PubMed database to focus on the evidence and management of errors in medical practice in general and in Neonatology in particular. We compared the results of the literature with our specific experience in Nina Simulation Centre (Pisa, Italy. Results: In Neonatology the main error domains are: medication and total parenteral nutrition, resuscitation and respiratory care, invasive procedures, nosocomial infections, patient identification, diagnostics. Risk factors include patients’ size, prematurity, vulnerability and underlying disease conditions but also multidisciplinary teams, working conditions providing fatigue, a large variety of treatment and investigative modalities needed. Discussion and Conclusions: In our opinion, it is hardly possible to change the human beings but it is likely possible to change the conditions under they work. Voluntary errors report systems can help in preventing adverse events. Education and re-training by means of simulation can be an effective strategy too. In Pisa (Italy Nina (ceNtro di FormazIone e SimulazioNe NeonAtale is a simulation center that offers the possibility of a continuous retraining for technical and non-technical skills to optimize neonatological care strategies. Furthermore, we have been working on a novel skill trainer for mechanical ventilation (MEchatronic REspiratory System SImulator for Neonatal Applications, MERESSINA. Finally, in our opinion national health policy indirectly influences risk for errors. Proceedings of the 9th International Workshop on Neonatology · Cagliari (Italy · October 23rd-26th, 2013 · Learned lessons, changing practice and cutting-edge research

A Hierarchical Bayes Error Correction Model to Explain Dynamic Effects of Price Changes

NARCIS (Netherlands)

D. Fok (Dennis); R. Paap (Richard); C. Horváth (Csilla); Ph.H.B.F. Franses (Philip Hans)

2005-01-01

textabstractThe authors put forward a sales response model to explain the differences in immediate and dynamic effects of promotional prices and regular prices on sales. The model consists of a vector autoregression rewritten in error-correction format which allows to disentangle the immediate

Sample presentation, sources of error and future perspectives on the application of vibrational spectroscopy in the wine industry.

Science.gov (United States)

Cozzolino, Daniel

2015-03-30

Vibrational spectroscopy encompasses a number of techniques and methods including ultra-violet, visible, Fourier transform infrared or mid infrared, near infrared and Raman spectroscopy. The use and application of spectroscopy generates spectra containing hundreds of variables (absorbances at each wavenumbers or wavelengths), resulting in the production of large data sets representing the chemical and biochemical wine fingerprint. Multivariate data analysis techniques are then required to handle the large amount of data generated in order to interpret the spectra in a meaningful way in order to develop a specific application. This paper focuses on the developments of sample presentation and main sources of error when vibrational spectroscopy methods are applied in wine analysis. Recent and novel applications will be discussed as examples of these developments. © 2014 Society of Chemical Industry.

Embracing Errors in Simulation-Based Training: The Effect of Error Training on Retention and Transfer of Central Venous Catheter Skills.

Science.gov (United States)

Gardner, Aimee K; Abdelfattah, Kareem; Wiersch, John; Ahmed, Rami A; Willis, Ross E

2015-01-01

Error management training is an approach that encourages exposure to errors during initial skill acquisition so that learners can be equipped with important error identification, management, and metacognitive skills. The purpose of this study was to determine how an error-focused training program affected performance, retention, and transfer of central venous catheter (CVC) placement skills when compared with traditional training methodologies. Surgical interns (N = 30) participated in a 1-hour session featuring an instructional video and practice performing internal jugular (IJ) and subclavian (SC) CVC placement with guided instruction. All interns underwent baseline knowledge and skill assessment for IJ and SC (pretest) CVC placement; watched a "correct-only" (CO) or "correct + error" (CE) instructional video; practiced for 30 minutes; and were posttested on knowledge and IJ and SC CVC placement. Skill retention and transfer (femoral CVC placement) were assessed 30 days later. All skills tests (pretest, posttest, and transfer) were videorecorded and deidentified for evaluation by a single blinded instructor using a validated 17-item checklist. Both the groups exhibited significant improvements (p error-based activities and discussions into training programs can be beneficial for skill retention and transfer. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Error threshold ghosts in a simple hypercycle with error prone self-replication

International Nuclear Information System (INIS)

Sardanyes, Josep